- published: 27 Mar 2016
- views: 111
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Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
- published: 03 Jul 2012
- views: 3553
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
- published: 30 Apr 2012
- views: 4001
Here is a lesson explaining when sentences have sense and when they have reference.
Explanation of deixis is also available.
There are exercises at the end of the video to test your understanding.
You are welcome to comment with any questions you have in mind :)
- published: 21 Jun 2016
- views: 1986
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "toothbrush" and "toothpaste" instead of a "teethbrush" and "teethpaste"? Sometimes, it looks like English makes no sense! I understand your frustration, so in this lesson, I will make sense of the senseless and look at some vocabulary that can confuse English learners.
TAKE THE QUIZ: http://www.engvid.com/10-words-in-english-that-dont-make-sense/
TRANSCRIPT
Hello out there? Hello? It's me. Oh, hello, hello, hello. Ronnie. Ronnie here. This is a really fun lesson, kind of something that I live for every day. One of my... It's not a hobby. One thing that I think is cool, generally and for real, are words in English. Being an English teacher, teaching you English, I come across words that just don't make sense. If you think of them in a different language, maybe your language, and then you translate it into English, it... What? It just does not make sense. So, I've got only 10 of these for you today, and I could go on with a thousand, but we are limited in our video time. So, today, 10 words, 10 things in English that just don't make sense.
First one. You have probably learned that in English, if you have: "in" or "un" or "anti" or "un" or "dis" before a word, it means not. So, your brain looks at this and says: "inflammable", "flammable". Okay. So, maybe you know the word, maybe you're French, maybe you know "flammable" or you can decide that "flame" means fire. So, if you look at this word in your logical brain, "inflammable" and "flammable" must mean the opposite. "Inflammable" must mean that something cannot catch fire, while as "flammable" must mean logically that something can catch fire. Guess what? Not in English. "Inflammable" and "flammable" both mean the same thing. What? So, the reason is "inflammable", sometimes the preposition... Not the prepositions. The things before the words can make it to do with it. So, actually "inflammable" means in flames. Do you know that band, In Flames? So, the prefix of "in"-it's a prefix-you know means not, but in this case, it means with or in, together. Mind.
Next one, this is fun: "noses run". Okay. So, you have a nose, it runs. This means that some liquid, which is called "mucus" or "snot", comes out of your nose. So, we say: "My nose is running. Ah, my nose is running." But: "Your feet smell." Is this funny yet? So, noses run and feet smell. This is another way how English is funny for me, because "feet smell" has two meanings. One, "smell" is a verb, and the other one: "Your feet smell bad." So, I can say: "My nose is running, and your feet smell." Because usually we run with our feet and we smell with our nose. Crazy. Good luck with this language.
The next one I've already kind of talked about, is: "mucus", "snot", or this word which is "phlegm". So, in your language-Japanese, Korean, Spanish-you probably... Not Spanish. But you probably say something close to "nose water", "hana sui". But guess what? In English, no. "Nose water" would be too easy. "Hana mizu", no way. We call it: "mucus", "snot", or "phlegm". We also have another word that's quite fun, it's called a "booger". A booger is something that you pick from your nose and you can flick. The mucus or the snot is the liquid, like the water. Nose water. It's nose water. So, mucus and snot is liquid, and the booger is more of a solid. Delicious. Okay.
Speaking about the nose, we have holes in our nose. Everyone probably has two. Yeah? Most people have two. Does anybody have one nostril out there? Because if you... You'd have to breathe double, I guess. Guess what? They're not called "nose holes", "hana no ana", mm-mm. They're called: "nostrils". Yeah, don't know why. It'd be easier if we just said: "Hey. My nose hole is really not doing too well over here." But we have to say: "My nostril is full of mucus." We can't say: "Hey. My nose hole is full of nose water." People would go: "Ah, cool. Want a Kleenex?" But no, no, we have to use these crazy words.
The other word, like in your language-Spanish "dedo", mm-hmm-you guys probably have something to do with your foot and a finger. Lots of languages you guys will probably say: "foot fingers", but not in English. We have to say: "toes". Hmm. "Foot fingers", it's really funny for me, because I've grown up my whole life knowing them as "toes", but "foot fingers" just makes more sense. English doesn't make sense.
On to the next five. If you have a car and you want to leave the car somewhere near your house, this place is called a "driveway". So, you park your car in a driveway. However, if you want to take your car someplace, like on a drive, you drive on a parkway. Obviously, it would make more sense if I park in my parkway and drive on the driveway, but again, this is why I have a job to teach you the crazy things, this is why learning English makes you crazy. Welcome to my world.
- published: 06 Oct 2016
- views: 223073
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss different types of meaning and sense relations.
- published: 18 Aug 2013
- views: 4985
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
- published: 03 Jul 2012
- views: 2050
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SENSE DISAMBIGUATION explanation.
Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license.
In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera.
The human brain is quite proficient at word-sense disambiguation. The fact that natural language is formed in a way that requires so much of it is a reflection of that neurologic reality. In other words, human language developed in a way that reflects (and also has helped to shape) the innate ability provided by the brain's neural networks. In computer science and the information technology that it enables, it has been a long-term challenge to develop the ability in computers to do natural language processing and machine learning.
To date, a rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date.
Accuracy of current algorithms is difficult to state without a host of caveats. In English, accuracy at the coarse-grained (homograph) level is routinely above 90%, with some methods on particular homographs achieving over 96%. On finer-grained sense distinctions, top accuracies from 59.1% to 69.0% have been reported in recent evaluation exercises (SemEval-2007, Senseval-2), where the baseline accuracy of the simplest possible algorithm of always choosing the most frequent sense was 51.4% and 57%, respectively.
Disambiguation requires two strict inputs: a dictionary to specify the senses which are to be disambiguated and a corpus of language data to be disambiguated (in some methods, a training corpus of language examples is also required). WSD task has two variants: "lexical sample" and "all words" task. The former comprises disambiguating the occurrences of a small sample of target words which were previously selected, while in the latter all the words in a piece of running text need to be disambiguated. The latter is deemed a more realistic form of evaluation, but the corpus is more expensive to produce because human annotators have to read the definitions for each word in the sequence every time they need to make a tagging judgement, rather than once for a block of instances for the same target word.
To give a hint how all this works, consider two examples of the distinct senses that exist for the (written) word "bass":
1. a type of fish
2. tones of low frequency
and the sentences:
1. I went fishing for some sea bass.
2. The bass line of the song is too weak.
To a human, it is obvious that the first sentence is using the word "bass (fish)", as in the former sense above and in the second sentence, the word "bass (instrument)" is being used as in the latter sense below. Developing algorithms to replicate this human ability can often be a difficult task, as is further exemplified by the implicit equivocation between "bass (sound)" and "bass (musical instrument)".
- published: 26 Jan 2017
- views: 1
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms.
Feel free to ask any questions in the comments.
- published: 04 Nov 2016
- views: 186
Word sense
In linguistics, a word sense is one of the meanings of a word. For example, a dictionary may have over 50 different senses of the word play, each of these having a different meaning based on the context of the word's usage in a sentence, as follows:
In each sentence we associate a different meaning of the word "play" based on hints the rest of the sentence gives us.
People and computers, as they read words, must use a process called word-sense disambiguation to find the correct meaning of a word. This process uses context to narrow the possible senses down to the probable ones. The context includes such things as the ideas conveyed by adjacent words and nearby phrases, the known or probable purpose and register of the conversation or document, and the orientation (time and place) implied or expressed. The disambiguation is thus context-sensitive.
A word sense may correspond to either a seme (the smallest unit of meaning) or a sememe (the next larger unit of meaning), and polysemy is the property of having multiple semes or sememes and thus multiple senses.
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Word_sense
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
Word-sense disambiguation
In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera.
The human brain is quite proficient at word-sense disambiguation. The fact that natural language is formed in a way that requires so much of it is a reflection of that neurologic reality. In other words, human language developed in a way that reflects (and also has helped to shape) the innate ability provided by the brain's neural networks. In computer science and the information technology that it enables, it has been a long-term challenge to develop the ability in computers to do natural language processing and machine learning.
To date, a rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date.
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Word-sense_disambiguation
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
Natural language processing
Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human–computer interaction. Many challenges in NLP involve natural language understanding, that is, enabling computers to derive meaning from human or natural language input, and others involve natural language generation.
History
The history of NLP generally starts in the 1950s, although work can be found from earlier periods. In 1950, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence.
The Georgetown experiment in 1954 involved fully automatic translation of more than sixty Russian sentences into English. The authors claimed that within three or five years, machine translation would be a solved problem. However, real progress was much slower, and after the ALPAC report in 1966, which found that ten-year-long research had failed to fulfill the expectations, funding for machine translation was dramatically reduced. Little further research in machine translation was conducted until the late 1980s, when the first statistical machine translation systems were developed.
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Natural_language_processing
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
Natural language
In neuropsychology, linguistics and the philosophy of language, a natural language or ordinary language is any language that develops naturally in humans through use and repetition (typically, in their first few years of life) without any conscious planning or premeditation of their own. Almost always, therefore, these are the languages human beings use to communicate with each other, whether by speech, signing, touch or writing. They are distinguished from constructed and formal languages such as those used to program computers or to study logic.
Defining natural language
Though the exact definition varies between scholars, natural language can broadly be defined in contrast to artificial or constructed languages (such as computer programming languages and international auxiliary languages) and to other communication systems in nature (such as bees' waggle dance). Definitions of "natural language" also usually state or imply that a "natural" language is one that any cognitively normal human infant is able to learn and whose development has been through use rather than by prescription. An unstandardized language such as African American Vernacular English, for example, is a natural language, whereas a standardized language such as Standard American English is, in part, prescribed.
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Natural_language
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
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20:07Word Sense Disambiguation - Natural Language Processing | Michigan
Word Sense Disambiguation - Natural Language Processing | MichiganWord Sense Disambiguation - Natural Language Processing | Michigan
-
46:40Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
Mod-01 Lec-29 Wordnet and Word Sense DisambiguationMod-01 Lec-29 Wordnet and Word Sense Disambiguation
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in -
11:5120 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/ Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/ Offered by Coursera: https://www.coursera.org/ -
8:16Semantics: Sense and Reference (Deixis)
Semantics: Sense and Reference (Deixis)Semantics: Sense and Reference (Deixis)
Here is a lesson explaining when sentences have sense and when they have reference. Explanation of deixis is also available. There are exercises at the end of the video to test your understanding. You are welcome to comment with any questions you have in mind :) -
11:5810 words in English that don't make sense! Hmmm...
10 words in English that don't make sense! Hmmm...10 words in English that don't make sense! Hmmm...
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "toothbrush" and "toothpaste" instead of a "teethbrush" and "teethpaste"? Sometimes, it looks like English makes no sense! I understand your frustration, so in this lesson, I will make sense of the senseless and look at some vocabulary that can confuse English learners. TAKE THE QUIZ: http://www.engvid.com/10-words-in-english-that-dont-make-sense/ TRANSCRIPT Hello out there? Hello? It's me. Oh, hello, hello, hello. Ronnie. Ronnie here. This is a really fun lesson, kind of something that I live for every day. One of my... It's not a hobby. One thing that I think is cool, generally and for real, are words in English. Being an English teacher, teaching you English, I come across words that just don't make sense. If you think of them in a different language, maybe your language, and then you translate it into English, it... What? It just does not make sense. So, I've got only 10 of these for you today, and I could go on with a thousand, but we are limited in our video time. So, today, 10 words, 10 things in English that just don't make sense. First one. You have probably learned that in English, if you have: "in" or "un" or "anti" or "un" or "dis" before a word, it means not. So, your brain looks at this and says: "inflammable", "flammable". Okay. So, maybe you know the word, maybe you're French, maybe you know "flammable" or you can decide that "flame" means fire. So, if you look at this word in your logical brain, "inflammable" and "flammable" must mean the opposite. "Inflammable" must mean that something cannot catch fire, while as "flammable" must mean logically that something can catch fire. Guess what? Not in English. "Inflammable" and "flammable" both mean the same thing. What? So, the reason is "inflammable", sometimes the preposition... Not the prepositions. The things before the words can make it to do with it. So, actually "inflammable" means in flames. Do you know that band, In Flames? So, the prefix of "in"-it's a prefix-you know means not, but in this case, it means with or in, together. Mind. Next one, this is fun: "noses run". Okay. So, you have a nose, it runs. This means that some liquid, which is called "mucus" or "snot", comes out of your nose. So, we say: "My nose is running. Ah, my nose is running." But: "Your feet smell." Is this funny yet? So, noses run and feet smell. This is another way how English is funny for me, because "feet smell" has two meanings. One, "smell" is a verb, and the other one: "Your feet smell bad." So, I can say: "My nose is running, and your feet smell." Because usually we run with our feet and we smell with our nose. Crazy. Good luck with this language. The next one I've already kind of talked about, is: "mucus", "snot", or this word which is "phlegm". So, in your language-Japanese, Korean, Spanish-you probably... Not Spanish. But you probably say something close to "nose water", "hana sui". But guess what? In English, no. "Nose water" would be too easy. "Hana mizu", no way. We call it: "mucus", "snot", or "phlegm". We also have another word that's quite fun, it's called a "booger". A booger is something that you pick from your nose and you can flick. The mucus or the snot is the liquid, like the water. Nose water. It's nose water. So, mucus and snot is liquid, and the booger is more of a solid. Delicious. Okay. Speaking about the nose, we have holes in our nose. Everyone probably has two. Yeah? Most people have two. Does anybody have one nostril out there? Because if you... You'd have to breathe double, I guess. Guess what? They're not called "nose holes", "hana no ana", mm-mm. They're called: "nostrils". Yeah, don't know why. It'd be easier if we just said: "Hey. My nose hole is really not doing too well over here." But we have to say: "My nostril is full of mucus." We can't say: "Hey. My nose hole is full of nose water." People would go: "Ah, cool. Want a Kleenex?" But no, no, we have to use these crazy words. The other word, like in your language-Spanish "dedo", mm-hmm-you guys probably have something to do with your foot and a finger. Lots of languages you guys will probably say: "foot fingers", but not in English. We have to say: "toes". Hmm. "Foot fingers", it's really funny for me, because I've grown up my whole life knowing them as "toes", but "foot fingers" just makes more sense. English doesn't make sense. On to the next five. If you have a car and you want to leave the car somewhere near your house, this place is called a "driveway". So, you park your car in a driveway. However, if you want to take your car someplace, like on a drive, you drive on a parkway. Obviously, it would make more sense if I park in my parkway and drive on the driveway, but again, this is why I have a job to teach you the crazy things, this is why learning English makes you crazy. Welcome to my world. -
23:55Sense relations
Sense relationsSense relations
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss different types of meaning and sense relations. -
43:10Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methodsMod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in -
4:20What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SENSE DISAMBIGUATION explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera. The human brain is quite proficient at word-sense disambiguation. The fact that natural language is formed in a way that requires so much of it is a reflection of that neurologic reality. In other words, human language developed in a way that reflects (and also has helped to shape) the innate ability provided by the brain's neural networks. In computer science and the information technology that it enables, it has been a long-term challenge to develop the ability in computers to do natural language processing and machine learning. To date, a rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date. Accuracy of current algorithms is difficult to state without a host of caveats. In English, accuracy at the coarse-grained (homograph) level is routinely above 90%, with some methods on particular homographs achieving over 96%. On finer-grained sense distinctions, top accuracies from 59.1% to 69.0% have been reported in recent evaluation exercises (SemEval-2007, Senseval-2), where the baseline accuracy of the simplest possible algorithm of always choosing the most frequent sense was 51.4% and 57%, respectively. Disambiguation requires two strict inputs: a dictionary to specify the senses which are to be disambiguated and a corpus of language data to be disambiguated (in some methods, a training corpus of language examples is also required). WSD task has two variants: "lexical sample" and "all words" task. The former comprises disambiguating the occurrences of a small sample of target words which were previously selected, while in the latter all the words in a piece of running text need to be disambiguated. The latter is deemed a more realistic form of evaluation, but the corpus is more expensive to produce because human annotators have to read the definitions for each word in the sequence every time they need to make a tagging judgement, rather than once for a block of instances for the same target word. To give a hint how all this works, consider two examples of the distinct senses that exist for the (written) word "bass": 1. a type of fish 2. tones of low frequency and the sentences: 1. I went fishing for some sea bass. 2. The bass line of the song is too weak. To a human, it is obvious that the first sentence is using the word "bass (fish)", as in the former sense above and in the second sentence, the word "bass (instrument)" is being used as in the latter sense below. Developing algorithms to replicate this human ability can often be a difficult task, as is further exemplified by the implicit equivocation between "bass (sound)" and "bass (musical instrument)". -
4:53Word Sense Disambiguation
Word Sense DisambiguationWord Sense Disambiguation
-
4:49Word Sense Relations: Synonyms
Word Sense Relations: SynonymsWord Sense Relations: Synonyms
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms. Feel free to ask any questions in the comments.
-
Word Sense Disambiguation - Natural Language Processing | Michigan
published: 27 Mar 2016 -
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
published: 03 Jul 2012 -
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/ Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/ Offered by Coursera: https://www.coursera.org/
published: 30 Apr 2012 -
Semantics: Sense and Reference (Deixis)
Here is a lesson explaining when sentences have sense and when they have reference. Explanation of deixis is also available. There are exercises at the end of the video to test your understanding. You are welcome to comment with any questions you have in mind :)
published: 21 Jun 2016 -
10 words in English that don't make sense! Hmmm...
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "toothbrush" and "toothpaste" instead of a "teethbrush" and "teethpaste"? Sometimes, it looks like English makes no sense! I understand your frustration, so in this lesson, I will make sense of the senseless and look at some vocabulary that can confuse English learners. TAKE THE QUIZ: http://www.engvid.com/10-words-in-english-that-dont-make-sense/ TRANSCRIPT Hello out there? Hello? It's me. Oh, hello, hello, hello. Ronnie. Ronnie here. This is a really fun lesson, kind of something that I live for every day. One of my... It's not a hobby. One thing that I think is cool, generally and for real, are words in English. Being an English ...
published: 06 Oct 2016 -
Sense relations
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss different types of meaning and sense relations.
published: 18 Aug 2013 -
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
published: 03 Jul 2012 -
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SENSE DISAMBIGUATION explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera. The human brain is quite proficient at word-sense disambiguation. The fact that na...
published: 26 Jan 2017 -
Word Sense Disambiguation
published: 08 Dec 2013 -
Word Sense Relations: Synonyms
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms. Feel free to ask any questions in the comments.
published: 04 Nov 2016
Word Sense Disambiguation - Natural Language Processing | Michigan
- Order: Reorder
- Duration: 20:07
- Updated: 27 Mar 2016
- views: 111
- published: 27 Mar 2016
- views: 111
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
- Order: Reorder
- Duration: 46:40
- Updated: 03 Jul 2012
- views: 3553
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel...
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
https://wn.com/Mod_01_Lec_29_Wordnet_And_Word_Sense_Disambiguation
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
- published: 03 Jul 2012
- views: 3553
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
- Order: Reorder
- Duration: 11:51
- Updated: 30 Apr 2012
- views: 4001
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online ...
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
https://wn.com/20_1_Word_Senses_And_Word_Relations_Nlp_Dan_Jurafsky_Chris_Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
- published: 30 Apr 2012
- views: 4001
Semantics: Sense and Reference (Deixis)
- Order: Reorder
- Duration: 8:16
- Updated: 21 Jun 2016
- views: 1986
Here is a lesson explaining when sentences have sense and when they have reference.
Explanation of deixis is also available.
There are exercises at the end o...
Here is a lesson explaining when sentences have sense and when they have reference.
Explanation of deixis is also available.
There are exercises at the end of the video to test your understanding.
You are welcome to comment with any questions you have in mind :)
https://wn.com/Semantics_Sense_And_Reference_(Deixis)
Here is a lesson explaining when sentences have sense and when they have reference.
Explanation of deixis is also available.
There are exercises at the end of the video to test your understanding.
You are welcome to comment with any questions you have in mind :)
- published: 21 Jun 2016
- views: 1986
10 words in English that don't make sense! Hmmm...
- Order: Reorder
- Duration: 11:58
- Updated: 06 Oct 2016
- views: 223073
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "t...
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "toothbrush" and "toothpaste" instead of a "teethbrush" and "teethpaste"? Sometimes, it looks like English makes no sense! I understand your frustration, so in this lesson, I will make sense of the senseless and look at some vocabulary that can confuse English learners.
TAKE THE QUIZ: http://www.engvid.com/10-words-in-english-that-dont-make-sense/
TRANSCRIPT
Hello out there? Hello? It's me. Oh, hello, hello, hello. Ronnie. Ronnie here. This is a really fun lesson, kind of something that I live for every day. One of my... It's not a hobby. One thing that I think is cool, generally and for real, are words in English. Being an English teacher, teaching you English, I come across words that just don't make sense. If you think of them in a different language, maybe your language, and then you translate it into English, it... What? It just does not make sense. So, I've got only 10 of these for you today, and I could go on with a thousand, but we are limited in our video time. So, today, 10 words, 10 things in English that just don't make sense.
First one. You have probably learned that in English, if you have: "in" or "un" or "anti" or "un" or "dis" before a word, it means not. So, your brain looks at this and says: "inflammable", "flammable". Okay. So, maybe you know the word, maybe you're French, maybe you know "flammable" or you can decide that "flame" means fire. So, if you look at this word in your logical brain, "inflammable" and "flammable" must mean the opposite. "Inflammable" must mean that something cannot catch fire, while as "flammable" must mean logically that something can catch fire. Guess what? Not in English. "Inflammable" and "flammable" both mean the same thing. What? So, the reason is "inflammable", sometimes the preposition... Not the prepositions. The things before the words can make it to do with it. So, actually "inflammable" means in flames. Do you know that band, In Flames? So, the prefix of "in"-it's a prefix-you know means not, but in this case, it means with or in, together. Mind.
Next one, this is fun: "noses run". Okay. So, you have a nose, it runs. This means that some liquid, which is called "mucus" or "snot", comes out of your nose. So, we say: "My nose is running. Ah, my nose is running." But: "Your feet smell." Is this funny yet? So, noses run and feet smell. This is another way how English is funny for me, because "feet smell" has two meanings. One, "smell" is a verb, and the other one: "Your feet smell bad." So, I can say: "My nose is running, and your feet smell." Because usually we run with our feet and we smell with our nose. Crazy. Good luck with this language.
The next one I've already kind of talked about, is: "mucus", "snot", or this word which is "phlegm". So, in your language-Japanese, Korean, Spanish-you probably... Not Spanish. But you probably say something close to "nose water", "hana sui". But guess what? In English, no. "Nose water" would be too easy. "Hana mizu", no way. We call it: "mucus", "snot", or "phlegm". We also have another word that's quite fun, it's called a "booger". A booger is something that you pick from your nose and you can flick. The mucus or the snot is the liquid, like the water. Nose water. It's nose water. So, mucus and snot is liquid, and the booger is more of a solid. Delicious. Okay.
Speaking about the nose, we have holes in our nose. Everyone probably has two. Yeah? Most people have two. Does anybody have one nostril out there? Because if you... You'd have to breathe double, I guess. Guess what? They're not called "nose holes", "hana no ana", mm-mm. They're called: "nostrils". Yeah, don't know why. It'd be easier if we just said: "Hey. My nose hole is really not doing too well over here." But we have to say: "My nostril is full of mucus." We can't say: "Hey. My nose hole is full of nose water." People would go: "Ah, cool. Want a Kleenex?" But no, no, we have to use these crazy words.
The other word, like in your language-Spanish "dedo", mm-hmm-you guys probably have something to do with your foot and a finger. Lots of languages you guys will probably say: "foot fingers", but not in English. We have to say: "toes". Hmm. "Foot fingers", it's really funny for me, because I've grown up my whole life knowing them as "toes", but "foot fingers" just makes more sense. English doesn't make sense.
On to the next five. If you have a car and you want to leave the car somewhere near your house, this place is called a "driveway". So, you park your car in a driveway. However, if you want to take your car someplace, like on a drive, you drive on a parkway. Obviously, it would make more sense if I park in my parkway and drive on the driveway, but again, this is why I have a job to teach you the crazy things, this is why learning English makes you crazy. Welcome to my world.
https://wn.com/10_Words_In_English_That_Don't_Make_Sense_Hmmm...
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "toothbrush" and "toothpaste" instead of a "teethbrush" and "teethpaste"? Sometimes, it looks like English makes no sense! I understand your frustration, so in this lesson, I will make sense of the senseless and look at some vocabulary that can confuse English learners.
TAKE THE QUIZ: http://www.engvid.com/10-words-in-english-that-dont-make-sense/
TRANSCRIPT
Hello out there? Hello? It's me. Oh, hello, hello, hello. Ronnie. Ronnie here. This is a really fun lesson, kind of something that I live for every day. One of my... It's not a hobby. One thing that I think is cool, generally and for real, are words in English. Being an English teacher, teaching you English, I come across words that just don't make sense. If you think of them in a different language, maybe your language, and then you translate it into English, it... What? It just does not make sense. So, I've got only 10 of these for you today, and I could go on with a thousand, but we are limited in our video time. So, today, 10 words, 10 things in English that just don't make sense.
First one. You have probably learned that in English, if you have: "in" or "un" or "anti" or "un" or "dis" before a word, it means not. So, your brain looks at this and says: "inflammable", "flammable". Okay. So, maybe you know the word, maybe you're French, maybe you know "flammable" or you can decide that "flame" means fire. So, if you look at this word in your logical brain, "inflammable" and "flammable" must mean the opposite. "Inflammable" must mean that something cannot catch fire, while as "flammable" must mean logically that something can catch fire. Guess what? Not in English. "Inflammable" and "flammable" both mean the same thing. What? So, the reason is "inflammable", sometimes the preposition... Not the prepositions. The things before the words can make it to do with it. So, actually "inflammable" means in flames. Do you know that band, In Flames? So, the prefix of "in"-it's a prefix-you know means not, but in this case, it means with or in, together. Mind.
Next one, this is fun: "noses run". Okay. So, you have a nose, it runs. This means that some liquid, which is called "mucus" or "snot", comes out of your nose. So, we say: "My nose is running. Ah, my nose is running." But: "Your feet smell." Is this funny yet? So, noses run and feet smell. This is another way how English is funny for me, because "feet smell" has two meanings. One, "smell" is a verb, and the other one: "Your feet smell bad." So, I can say: "My nose is running, and your feet smell." Because usually we run with our feet and we smell with our nose. Crazy. Good luck with this language.
The next one I've already kind of talked about, is: "mucus", "snot", or this word which is "phlegm". So, in your language-Japanese, Korean, Spanish-you probably... Not Spanish. But you probably say something close to "nose water", "hana sui". But guess what? In English, no. "Nose water" would be too easy. "Hana mizu", no way. We call it: "mucus", "snot", or "phlegm". We also have another word that's quite fun, it's called a "booger". A booger is something that you pick from your nose and you can flick. The mucus or the snot is the liquid, like the water. Nose water. It's nose water. So, mucus and snot is liquid, and the booger is more of a solid. Delicious. Okay.
Speaking about the nose, we have holes in our nose. Everyone probably has two. Yeah? Most people have two. Does anybody have one nostril out there? Because if you... You'd have to breathe double, I guess. Guess what? They're not called "nose holes", "hana no ana", mm-mm. They're called: "nostrils". Yeah, don't know why. It'd be easier if we just said: "Hey. My nose hole is really not doing too well over here." But we have to say: "My nostril is full of mucus." We can't say: "Hey. My nose hole is full of nose water." People would go: "Ah, cool. Want a Kleenex?" But no, no, we have to use these crazy words.
The other word, like in your language-Spanish "dedo", mm-hmm-you guys probably have something to do with your foot and a finger. Lots of languages you guys will probably say: "foot fingers", but not in English. We have to say: "toes". Hmm. "Foot fingers", it's really funny for me, because I've grown up my whole life knowing them as "toes", but "foot fingers" just makes more sense. English doesn't make sense.
On to the next five. If you have a car and you want to leave the car somewhere near your house, this place is called a "driveway". So, you park your car in a driveway. However, if you want to take your car someplace, like on a drive, you drive on a parkway. Obviously, it would make more sense if I park in my parkway and drive on the driveway, but again, this is why I have a job to teach you the crazy things, this is why learning English makes you crazy. Welcome to my world.
- published: 06 Oct 2016
- views: 223073
Sense relations
- Order: Reorder
- Duration: 23:55
- Updated: 18 Aug 2013
- views: 4985
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss differ...
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss different types of meaning and sense relations.
https://wn.com/Sense_Relations
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss different types of meaning and sense relations.
- published: 18 Aug 2013
- views: 4985
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
- Order: Reorder
- Duration: 43:10
- Updated: 03 Jul 2012
- views: 2050
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel...
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
https://wn.com/Mod_01_Lec_34_Word_Sense_Disambiguation_Supervised_And_Unsupervised_Methods
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
- published: 03 Jul 2012
- views: 2050
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
- Order: Reorder
- Duration: 4:20
- Updated: 26 Jan 2017
- views: 1
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SEN...
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SENSE DISAMBIGUATION explanation.
Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license.
In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera.
The human brain is quite proficient at word-sense disambiguation. The fact that natural language is formed in a way that requires so much of it is a reflection of that neurologic reality. In other words, human language developed in a way that reflects (and also has helped to shape) the innate ability provided by the brain's neural networks. In computer science and the information technology that it enables, it has been a long-term challenge to develop the ability in computers to do natural language processing and machine learning.
To date, a rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date.
Accuracy of current algorithms is difficult to state without a host of caveats. In English, accuracy at the coarse-grained (homograph) level is routinely above 90%, with some methods on particular homographs achieving over 96%. On finer-grained sense distinctions, top accuracies from 59.1% to 69.0% have been reported in recent evaluation exercises (SemEval-2007, Senseval-2), where the baseline accuracy of the simplest possible algorithm of always choosing the most frequent sense was 51.4% and 57%, respectively.
Disambiguation requires two strict inputs: a dictionary to specify the senses which are to be disambiguated and a corpus of language data to be disambiguated (in some methods, a training corpus of language examples is also required). WSD task has two variants: "lexical sample" and "all words" task. The former comprises disambiguating the occurrences of a small sample of target words which were previously selected, while in the latter all the words in a piece of running text need to be disambiguated. The latter is deemed a more realistic form of evaluation, but the corpus is more expensive to produce because human annotators have to read the definitions for each word in the sequence every time they need to make a tagging judgement, rather than once for a block of instances for the same target word.
To give a hint how all this works, consider two examples of the distinct senses that exist for the (written) word "bass":
1. a type of fish
2. tones of low frequency
and the sentences:
1. I went fishing for some sea bass.
2. The bass line of the song is too weak.
To a human, it is obvious that the first sentence is using the word "bass (fish)", as in the former sense above and in the second sentence, the word "bass (instrument)" is being used as in the latter sense below. Developing algorithms to replicate this human ability can often be a difficult task, as is further exemplified by the implicit equivocation between "bass (sound)" and "bass (musical instrument)".
https://wn.com/What_Is_Word_Sense_Disambiguation_What_Does_Word_Sense_Disambiguation_Mean
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SENSE DISAMBIGUATION explanation.
Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license.
In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera.
The human brain is quite proficient at word-sense disambiguation. The fact that natural language is formed in a way that requires so much of it is a reflection of that neurologic reality. In other words, human language developed in a way that reflects (and also has helped to shape) the innate ability provided by the brain's neural networks. In computer science and the information technology that it enables, it has been a long-term challenge to develop the ability in computers to do natural language processing and machine learning.
To date, a rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date.
Accuracy of current algorithms is difficult to state without a host of caveats. In English, accuracy at the coarse-grained (homograph) level is routinely above 90%, with some methods on particular homographs achieving over 96%. On finer-grained sense distinctions, top accuracies from 59.1% to 69.0% have been reported in recent evaluation exercises (SemEval-2007, Senseval-2), where the baseline accuracy of the simplest possible algorithm of always choosing the most frequent sense was 51.4% and 57%, respectively.
Disambiguation requires two strict inputs: a dictionary to specify the senses which are to be disambiguated and a corpus of language data to be disambiguated (in some methods, a training corpus of language examples is also required). WSD task has two variants: "lexical sample" and "all words" task. The former comprises disambiguating the occurrences of a small sample of target words which were previously selected, while in the latter all the words in a piece of running text need to be disambiguated. The latter is deemed a more realistic form of evaluation, but the corpus is more expensive to produce because human annotators have to read the definitions for each word in the sequence every time they need to make a tagging judgement, rather than once for a block of instances for the same target word.
To give a hint how all this works, consider two examples of the distinct senses that exist for the (written) word "bass":
1. a type of fish
2. tones of low frequency
and the sentences:
1. I went fishing for some sea bass.
2. The bass line of the song is too weak.
To a human, it is obvious that the first sentence is using the word "bass (fish)", as in the former sense above and in the second sentence, the word "bass (instrument)" is being used as in the latter sense below. Developing algorithms to replicate this human ability can often be a difficult task, as is further exemplified by the implicit equivocation between "bass (sound)" and "bass (musical instrument)".
- published: 26 Jan 2017
- views: 1
Word Sense Disambiguation
- Order: Reorder
- Duration: 4:53
- Updated: 08 Dec 2013
- views: 449
- published: 08 Dec 2013
- views: 449
Word Sense Relations: Synonyms
- Order: Reorder
- Duration: 4:49
- Updated: 04 Nov 2016
- views: 186
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms.
Feel free to ask any questions in the comments.
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms.
Feel free to ask any questions in the comments.
https://wn.com/Word_Sense_Relations_Synonyms
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms.
Feel free to ask any questions in the comments.
- published: 04 Nov 2016
- views: 186
-
Word Sense Disambiguation - Natural Language Processing | Michigan
published: 27 Mar 2016 -
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
published: 03 Jul 2012 -
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/ Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/ Offered by Coursera: https://www.coursera.org/
published: 30 Apr 2012 -
Semantics: Sense and Reference (Deixis)
Here is a lesson explaining when sentences have sense and when they have reference. Explanation of deixis is also available. There are exercises at the end of the video to test your understanding. You are welcome to comment with any questions you have in mind :)
published: 21 Jun 2016 -
10 words in English that don't make sense! Hmmm...
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "toothbrush" and "toothpaste" instead of a "teethbrush" and "teethpaste"? Sometimes, it looks like English makes no sense! I understand your frustration, so in this lesson, I will make sense of the senseless and look at some vocabulary that can confuse English learners. TAKE THE QUIZ: http://www.engvid.com/10-words-in-english-that-dont-make-sense/ TRANSCRIPT Hello out there? Hello? It's me. Oh, hello, hello, hello. Ronnie. Ronnie here. This is a really fun lesson, kind of something that I live for every day. One of my... It's not a hobby. One thing that I think is cool, generally and for real, are words in English. Being an English ...
published: 06 Oct 2016 -
Sense relations
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss different types of meaning and sense relations.
published: 18 Aug 2013 -
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
published: 03 Jul 2012 -
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SENSE DISAMBIGUATION explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera. The human brain is quite proficient at word-sense disambiguation. The fact that na...
published: 26 Jan 2017 -
Word Sense Disambiguation
published: 08 Dec 2013 -
Word Sense Relations: Synonyms
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms. Feel free to ask any questions in the comments.
published: 04 Nov 2016
Word Sense Disambiguation - Natural Language Processing | Michigan
- Order: Reorder
- Duration: 20:07
- Updated: 27 Mar 2016
- views: 111
- published: 27 Mar 2016
- views: 111
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
- Order: Reorder
- Duration: 46:40
- Updated: 03 Jul 2012
- views: 3553
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel...
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
https://wn.com/Mod_01_Lec_29_Wordnet_And_Word_Sense_Disambiguation
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
- published: 03 Jul 2012
- views: 3553
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
- Order: Reorder
- Duration: 11:51
- Updated: 30 Apr 2012
- views: 4001
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online ...
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
https://wn.com/20_1_Word_Senses_And_Word_Relations_Nlp_Dan_Jurafsky_Chris_Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.com/
Professor Dan Jurafsky & Chris Manning are offering a free online course on Natural Language Processing starting in March 19, 2012. http://www.nlp-class.org/
Offered by Coursera: https://www.coursera.org/
- published: 30 Apr 2012
- views: 4001
Semantics: Sense and Reference (Deixis)
- Order: Reorder
- Duration: 8:16
- Updated: 21 Jun 2016
- views: 1986
Here is a lesson explaining when sentences have sense and when they have reference.
Explanation of deixis is also available.
There are exercises at the end o...
Here is a lesson explaining when sentences have sense and when they have reference.
Explanation of deixis is also available.
There are exercises at the end of the video to test your understanding.
You are welcome to comment with any questions you have in mind :)
https://wn.com/Semantics_Sense_And_Reference_(Deixis)
Here is a lesson explaining when sentences have sense and when they have reference.
Explanation of deixis is also available.
There are exercises at the end of the video to test your understanding.
You are welcome to comment with any questions you have in mind :)
- published: 21 Jun 2016
- views: 1986
10 words in English that don't make sense! Hmmm...
- Order: Reorder
- Duration: 11:58
- Updated: 06 Oct 2016
- views: 223073
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "t...
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "toothbrush" and "toothpaste" instead of a "teethbrush" and "teethpaste"? Sometimes, it looks like English makes no sense! I understand your frustration, so in this lesson, I will make sense of the senseless and look at some vocabulary that can confuse English learners.
TAKE THE QUIZ: http://www.engvid.com/10-words-in-english-that-dont-make-sense/
TRANSCRIPT
Hello out there? Hello? It's me. Oh, hello, hello, hello. Ronnie. Ronnie here. This is a really fun lesson, kind of something that I live for every day. One of my... It's not a hobby. One thing that I think is cool, generally and for real, are words in English. Being an English teacher, teaching you English, I come across words that just don't make sense. If you think of them in a different language, maybe your language, and then you translate it into English, it... What? It just does not make sense. So, I've got only 10 of these for you today, and I could go on with a thousand, but we are limited in our video time. So, today, 10 words, 10 things in English that just don't make sense.
First one. You have probably learned that in English, if you have: "in" or "un" or "anti" or "un" or "dis" before a word, it means not. So, your brain looks at this and says: "inflammable", "flammable". Okay. So, maybe you know the word, maybe you're French, maybe you know "flammable" or you can decide that "flame" means fire. So, if you look at this word in your logical brain, "inflammable" and "flammable" must mean the opposite. "Inflammable" must mean that something cannot catch fire, while as "flammable" must mean logically that something can catch fire. Guess what? Not in English. "Inflammable" and "flammable" both mean the same thing. What? So, the reason is "inflammable", sometimes the preposition... Not the prepositions. The things before the words can make it to do with it. So, actually "inflammable" means in flames. Do you know that band, In Flames? So, the prefix of "in"-it's a prefix-you know means not, but in this case, it means with or in, together. Mind.
Next one, this is fun: "noses run". Okay. So, you have a nose, it runs. This means that some liquid, which is called "mucus" or "snot", comes out of your nose. So, we say: "My nose is running. Ah, my nose is running." But: "Your feet smell." Is this funny yet? So, noses run and feet smell. This is another way how English is funny for me, because "feet smell" has two meanings. One, "smell" is a verb, and the other one: "Your feet smell bad." So, I can say: "My nose is running, and your feet smell." Because usually we run with our feet and we smell with our nose. Crazy. Good luck with this language.
The next one I've already kind of talked about, is: "mucus", "snot", or this word which is "phlegm". So, in your language-Japanese, Korean, Spanish-you probably... Not Spanish. But you probably say something close to "nose water", "hana sui". But guess what? In English, no. "Nose water" would be too easy. "Hana mizu", no way. We call it: "mucus", "snot", or "phlegm". We also have another word that's quite fun, it's called a "booger". A booger is something that you pick from your nose and you can flick. The mucus or the snot is the liquid, like the water. Nose water. It's nose water. So, mucus and snot is liquid, and the booger is more of a solid. Delicious. Okay.
Speaking about the nose, we have holes in our nose. Everyone probably has two. Yeah? Most people have two. Does anybody have one nostril out there? Because if you... You'd have to breathe double, I guess. Guess what? They're not called "nose holes", "hana no ana", mm-mm. They're called: "nostrils". Yeah, don't know why. It'd be easier if we just said: "Hey. My nose hole is really not doing too well over here." But we have to say: "My nostril is full of mucus." We can't say: "Hey. My nose hole is full of nose water." People would go: "Ah, cool. Want a Kleenex?" But no, no, we have to use these crazy words.
The other word, like in your language-Spanish "dedo", mm-hmm-you guys probably have something to do with your foot and a finger. Lots of languages you guys will probably say: "foot fingers", but not in English. We have to say: "toes". Hmm. "Foot fingers", it's really funny for me, because I've grown up my whole life knowing them as "toes", but "foot fingers" just makes more sense. English doesn't make sense.
On to the next five. If you have a car and you want to leave the car somewhere near your house, this place is called a "driveway". So, you park your car in a driveway. However, if you want to take your car someplace, like on a drive, you drive on a parkway. Obviously, it would make more sense if I park in my parkway and drive on the driveway, but again, this is why I have a job to teach you the crazy things, this is why learning English makes you crazy. Welcome to my world.
https://wn.com/10_Words_In_English_That_Don't_Make_Sense_Hmmm...
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we have "toes", not "footfingers"? And why do we brush our teeth with a "toothbrush" and "toothpaste" instead of a "teethbrush" and "teethpaste"? Sometimes, it looks like English makes no sense! I understand your frustration, so in this lesson, I will make sense of the senseless and look at some vocabulary that can confuse English learners.
TAKE THE QUIZ: http://www.engvid.com/10-words-in-english-that-dont-make-sense/
TRANSCRIPT
Hello out there? Hello? It's me. Oh, hello, hello, hello. Ronnie. Ronnie here. This is a really fun lesson, kind of something that I live for every day. One of my... It's not a hobby. One thing that I think is cool, generally and for real, are words in English. Being an English teacher, teaching you English, I come across words that just don't make sense. If you think of them in a different language, maybe your language, and then you translate it into English, it... What? It just does not make sense. So, I've got only 10 of these for you today, and I could go on with a thousand, but we are limited in our video time. So, today, 10 words, 10 things in English that just don't make sense.
First one. You have probably learned that in English, if you have: "in" or "un" or "anti" or "un" or "dis" before a word, it means not. So, your brain looks at this and says: "inflammable", "flammable". Okay. So, maybe you know the word, maybe you're French, maybe you know "flammable" or you can decide that "flame" means fire. So, if you look at this word in your logical brain, "inflammable" and "flammable" must mean the opposite. "Inflammable" must mean that something cannot catch fire, while as "flammable" must mean logically that something can catch fire. Guess what? Not in English. "Inflammable" and "flammable" both mean the same thing. What? So, the reason is "inflammable", sometimes the preposition... Not the prepositions. The things before the words can make it to do with it. So, actually "inflammable" means in flames. Do you know that band, In Flames? So, the prefix of "in"-it's a prefix-you know means not, but in this case, it means with or in, together. Mind.
Next one, this is fun: "noses run". Okay. So, you have a nose, it runs. This means that some liquid, which is called "mucus" or "snot", comes out of your nose. So, we say: "My nose is running. Ah, my nose is running." But: "Your feet smell." Is this funny yet? So, noses run and feet smell. This is another way how English is funny for me, because "feet smell" has two meanings. One, "smell" is a verb, and the other one: "Your feet smell bad." So, I can say: "My nose is running, and your feet smell." Because usually we run with our feet and we smell with our nose. Crazy. Good luck with this language.
The next one I've already kind of talked about, is: "mucus", "snot", or this word which is "phlegm". So, in your language-Japanese, Korean, Spanish-you probably... Not Spanish. But you probably say something close to "nose water", "hana sui". But guess what? In English, no. "Nose water" would be too easy. "Hana mizu", no way. We call it: "mucus", "snot", or "phlegm". We also have another word that's quite fun, it's called a "booger". A booger is something that you pick from your nose and you can flick. The mucus or the snot is the liquid, like the water. Nose water. It's nose water. So, mucus and snot is liquid, and the booger is more of a solid. Delicious. Okay.
Speaking about the nose, we have holes in our nose. Everyone probably has two. Yeah? Most people have two. Does anybody have one nostril out there? Because if you... You'd have to breathe double, I guess. Guess what? They're not called "nose holes", "hana no ana", mm-mm. They're called: "nostrils". Yeah, don't know why. It'd be easier if we just said: "Hey. My nose hole is really not doing too well over here." But we have to say: "My nostril is full of mucus." We can't say: "Hey. My nose hole is full of nose water." People would go: "Ah, cool. Want a Kleenex?" But no, no, we have to use these crazy words.
The other word, like in your language-Spanish "dedo", mm-hmm-you guys probably have something to do with your foot and a finger. Lots of languages you guys will probably say: "foot fingers", but not in English. We have to say: "toes". Hmm. "Foot fingers", it's really funny for me, because I've grown up my whole life knowing them as "toes", but "foot fingers" just makes more sense. English doesn't make sense.
On to the next five. If you have a car and you want to leave the car somewhere near your house, this place is called a "driveway". So, you park your car in a driveway. However, if you want to take your car someplace, like on a drive, you drive on a parkway. Obviously, it would make more sense if I park in my parkway and drive on the driveway, but again, this is why I have a job to teach you the crazy things, this is why learning English makes you crazy. Welcome to my world.
- published: 06 Oct 2016
- views: 223073
Sense relations
- Order: Reorder
- Duration: 23:55
- Updated: 18 Aug 2013
- views: 4985
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss differ...
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss different types of meaning and sense relations.
https://wn.com/Sense_Relations
This video lecture is a part of the course 'An Introduction to English Linguistics' at the University of Neuchâtel. This is session 9, in which I discuss different types of meaning and sense relations.
- published: 18 Aug 2013
- views: 4985
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
- Order: Reorder
- Duration: 43:10
- Updated: 03 Jul 2012
- views: 2050
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel...
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
https://wn.com/Mod_01_Lec_34_Word_Sense_Disambiguation_Supervised_And_Unsupervised_Methods
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science & Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.iitm.ac.in
- published: 03 Jul 2012
- views: 2050
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
- Order: Reorder
- Duration: 4:20
- Updated: 26 Jan 2017
- views: 1
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SEN...
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SENSE DISAMBIGUATION explanation.
Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license.
In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera.
The human brain is quite proficient at word-sense disambiguation. The fact that natural language is formed in a way that requires so much of it is a reflection of that neurologic reality. In other words, human language developed in a way that reflects (and also has helped to shape) the innate ability provided by the brain's neural networks. In computer science and the information technology that it enables, it has been a long-term challenge to develop the ability in computers to do natural language processing and machine learning.
To date, a rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date.
Accuracy of current algorithms is difficult to state without a host of caveats. In English, accuracy at the coarse-grained (homograph) level is routinely above 90%, with some methods on particular homographs achieving over 96%. On finer-grained sense distinctions, top accuracies from 59.1% to 69.0% have been reported in recent evaluation exercises (SemEval-2007, Senseval-2), where the baseline accuracy of the simplest possible algorithm of always choosing the most frequent sense was 51.4% and 57%, respectively.
Disambiguation requires two strict inputs: a dictionary to specify the senses which are to be disambiguated and a corpus of language data to be disambiguated (in some methods, a training corpus of language examples is also required). WSD task has two variants: "lexical sample" and "all words" task. The former comprises disambiguating the occurrences of a small sample of target words which were previously selected, while in the latter all the words in a piece of running text need to be disambiguated. The latter is deemed a more realistic form of evaluation, but the corpus is more expensive to produce because human annotators have to read the definitions for each word in the sequence every time they need to make a tagging judgement, rather than once for a block of instances for the same target word.
To give a hint how all this works, consider two examples of the distinct senses that exist for the (written) word "bass":
1. a type of fish
2. tones of low frequency
and the sentences:
1. I went fishing for some sea bass.
2. The bass line of the song is too weak.
To a human, it is obvious that the first sentence is using the word "bass (fish)", as in the former sense above and in the second sentence, the word "bass (instrument)" is being used as in the latter sense below. Developing algorithms to replicate this human ability can often be a difficult task, as is further exemplified by the implicit equivocation between "bass (sound)" and "bass (musical instrument)".
https://wn.com/What_Is_Word_Sense_Disambiguation_What_Does_Word_Sense_Disambiguation_Mean
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DISAMBIGUATION meaning - WORD-SENSE DISAMBIGUATION definition - WORD-SENSE DISAMBIGUATION explanation.
Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license.
In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e. meaning) is used in a sentence, when the word has multiple meanings. The solution to this problem impacts other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, inference et cetera.
The human brain is quite proficient at word-sense disambiguation. The fact that natural language is formed in a way that requires so much of it is a reflection of that neurologic reality. In other words, human language developed in a way that reflects (and also has helped to shape) the innate ability provided by the brain's neural networks. In computer science and the information technology that it enables, it has been a long-term challenge to develop the ability in computers to do natural language processing and machine learning.
To date, a rich variety of techniques have been researched, from dictionary-based methods that use the knowledge encoded in lexical resources, to supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, to completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date.
Accuracy of current algorithms is difficult to state without a host of caveats. In English, accuracy at the coarse-grained (homograph) level is routinely above 90%, with some methods on particular homographs achieving over 96%. On finer-grained sense distinctions, top accuracies from 59.1% to 69.0% have been reported in recent evaluation exercises (SemEval-2007, Senseval-2), where the baseline accuracy of the simplest possible algorithm of always choosing the most frequent sense was 51.4% and 57%, respectively.
Disambiguation requires two strict inputs: a dictionary to specify the senses which are to be disambiguated and a corpus of language data to be disambiguated (in some methods, a training corpus of language examples is also required). WSD task has two variants: "lexical sample" and "all words" task. The former comprises disambiguating the occurrences of a small sample of target words which were previously selected, while in the latter all the words in a piece of running text need to be disambiguated. The latter is deemed a more realistic form of evaluation, but the corpus is more expensive to produce because human annotators have to read the definitions for each word in the sequence every time they need to make a tagging judgement, rather than once for a block of instances for the same target word.
To give a hint how all this works, consider two examples of the distinct senses that exist for the (written) word "bass":
1. a type of fish
2. tones of low frequency
and the sentences:
1. I went fishing for some sea bass.
2. The bass line of the song is too weak.
To a human, it is obvious that the first sentence is using the word "bass (fish)", as in the former sense above and in the second sentence, the word "bass (instrument)" is being used as in the latter sense below. Developing algorithms to replicate this human ability can often be a difficult task, as is further exemplified by the implicit equivocation between "bass (sound)" and "bass (musical instrument)".
- published: 26 Jan 2017
- views: 1
Word Sense Disambiguation
- Order: Reorder
- Duration: 4:53
- Updated: 08 Dec 2013
- views: 449
- published: 08 Dec 2013
- views: 449
Word Sense Relations: Synonyms
- Order: Reorder
- Duration: 4:49
- Updated: 04 Nov 2016
- views: 186
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms.
Feel free to ask any questions in the comments.
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms.
Feel free to ask any questions in the comments.
https://wn.com/Word_Sense_Relations_Synonyms
This video illustrates the different types of synonyms and shows why some words cannot be complete synonyms.
Feel free to ask any questions in the comments.
- published: 04 Nov 2016
- views: 186
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Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
published: 14 Oct 2016 -
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
published: 14 Oct 2016 -
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For ... Sensing Murder Full Episodes Sensing Murder Full Episodes Sensing Murder Full Episodes Sensing Murder Full Episodes Sensing Murder Full Episodes. Spirited teenager Jayne Furlong dreamed of becoming a child psychologist - instead, she ended up a prostitute. In 1993, 17 year old Jayne vanished from her ... Sensing Murder Full Episodes Sensing Murde Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words
published: 19 Jul 2015 -
Natural Language Processing Lecture 32 Word Sense Disambiguation
published: 16 Apr 2015 -
Natural Language Processing Lecture 30 Wordnet and Word Sense Disambiguationcontd…
published: 16 Apr 2015 -
Natural Language Processing Lecture 29 Wordnet and Word Sense Disambiguation
published: 16 Apr 2015 -
Natural Language Processing Lecture 31 Wordnet; Metonymy and Word Sense Disambiguation
published: 16 Apr 2015 -
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguation)
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguation). Dated: 11/12/2014
published: 22 Nov 2016 -
Sensing Murder S02E06 Lost For Words Full Episode
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For . Spirited teenager Jayne Furlong dreamed of becoming a child psychologist - instead, she ended up a prostitute. In 1993, 17 year old Jayne vanished from her.
published: 08 Nov 2016 -
Sensing Murder S02E06 Lost For Words Full Episode
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For . Spirited teenager Jayne Furlong dreamed of becoming a child psychologist - instead, she ended up a prostitute. In 1993, 17 year old Jayne vanished from her.
published: 15 Oct 2016
Sensing Murder S02E06 Lost For Words
- Order: Reorder
- Duration: 1:04:36
- Updated: 14 Oct 2016
- views: 422
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
https://wn.com/Sensing_Murder_S02E06_Lost_For_Words
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
- published: 14 Oct 2016
- views: 422
Sensing Murder S02E06 Lost For Words
- Order: Reorder
- Duration: 1:04:36
- Updated: 14 Oct 2016
- views: 12
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
https://wn.com/Sensing_Murder_S02E06_Lost_For_Words
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
- published: 14 Oct 2016
- views: 12
Sensing Murder S02E06 Lost For Words
- Order: Reorder
- Duration: 1:04:36
- Updated: 19 Jul 2015
- views: 25023
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For ...
Sensing Mu...
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For ...
Sensing Murder Full Episodes Sensing Murder Full Episodes Sensing Murder Full Episodes Sensing Murder Full Episodes Sensing Murder Full Episodes.
Spirited teenager Jayne Furlong dreamed of becoming a child psychologist - instead, she ended up a prostitute. In 1993, 17 year old Jayne vanished from her ...
Sensing Murder Full Episodes Sensing Murde
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words
https://wn.com/Sensing_Murder_S02E06_Lost_For_Words
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For ...
Sensing Murder Full Episodes Sensing Murder Full Episodes Sensing Murder Full Episodes Sensing Murder Full Episodes Sensing Murder Full Episodes.
Spirited teenager Jayne Furlong dreamed of becoming a child psychologist - instead, she ended up a prostitute. In 1993, 17 year old Jayne vanished from her ...
Sensing Murder Full Episodes Sensing Murde
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words
- published: 19 Jul 2015
- views: 25023
Natural Language Processing Lecture 32 Word Sense Disambiguation
- Order: Reorder
- Duration: 49:07
- Updated: 16 Apr 2015
- views: 46
- published: 16 Apr 2015
- views: 46
Natural Language Processing Lecture 30 Wordnet and Word Sense Disambiguationcontd…
- Order: Reorder
- Duration: 47:23
- Updated: 16 Apr 2015
- views: 38
- published: 16 Apr 2015
- views: 38
Natural Language Processing Lecture 29 Wordnet and Word Sense Disambiguation
- Order: Reorder
- Duration: 46:40
- Updated: 16 Apr 2015
- views: 110
- published: 16 Apr 2015
- views: 110
Natural Language Processing Lecture 31 Wordnet; Metonymy and Word Sense Disambiguation
- Order: Reorder
- Duration: 49:16
- Updated: 16 Apr 2015
- views: 27
- published: 16 Apr 2015
- views: 27
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguation)
- Order: Reorder
- Duration: 1:29:34
- Updated: 22 Nov 2016
- views: 33
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguation).
Dated: 11/12/2014
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguation).
Dated: 11/12/2014
https://wn.com/Empirical_Methods_In_Nlp_(Lecture_6_Lexical_Knowledge_Network_And_Word_Sense_Disambiguation)
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguation).
Dated: 11/12/2014
- published: 22 Nov 2016
- views: 33
Sensing Murder S02E06 Lost For Words Full Episode
- Order: Reorder
- Duration: 2:48:59
- Updated: 08 Nov 2016
- views: 0
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
Spirited teen...
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
Spirited teenager Jayne Furlong dreamed of becoming a child psychologist - instead, she ended up a prostitute. In 1993, 17 year old Jayne vanished from her.
https://wn.com/Sensing_Murder_S02E06_Lost_For_Words_Full_Episode
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
Spirited teenager Jayne Furlong dreamed of becoming a child psychologist - instead, she ended up a prostitute. In 1993, 17 year old Jayne vanished from her.
- published: 08 Nov 2016
- views: 0
Sensing Murder S02E06 Lost For Words Full Episode
- Order: Reorder
- Duration: 2:38:09
- Updated: 15 Oct 2016
- views: 8
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
Spirited teen...
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
Spirited teenager Jayne Furlong dreamed of becoming a child psychologist - instead, she ended up a prostitute. In 1993, 17 year old Jayne vanished from her.
https://wn.com/Sensing_Murder_S02E06_Lost_For_Words_Full_Episode
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For .
Spirited teenager Jayne Furlong dreamed of becoming a child psychologist - instead, she ended up a prostitute. In 1993, 17 year old Jayne vanished from her.
- published: 15 Oct 2016
- views: 8
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20:07
Word Sense Disambiguation - Natural Language Processing | Michigan
published: 27 Mar 2016
Word Sense Disambiguation - Natural Language Processing | Michigan
Word Sense Disambiguation - Natural Language Processing | Michigan
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- published: 27 Mar 2016
- views: 111
46:40
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science...
published: 03 Jul 2012
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
- Report rights infringement
- published: 03 Jul 2012
- views: 3553
11:51
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.c...
published: 30 Apr 2012
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
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- published: 30 Apr 2012
- views: 4001
8:16
Semantics: Sense and Reference (Deixis)
Here is a lesson explaining when sentences have sense and when they have reference.
Expl...
published: 21 Jun 2016
Semantics: Sense and Reference (Deixis)
Semantics: Sense and Reference (Deixis)
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- published: 21 Jun 2016
- views: 1986
11:58
10 words in English that don't make sense! Hmmm...
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we h...
published: 06 Oct 2016
10 words in English that don't make sense! Hmmm...
10 words in English that don't make sense! Hmmm...
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- published: 06 Oct 2016
- views: 223073
23:55
Sense relations
This video lecture is a part of the course 'An Introduction to English Linguistics' at the...
published: 18 Aug 2013
Sense relations
Sense relations
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- views: 4985
43:10
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science...
published: 03 Jul 2012
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
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4:20
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DI...
published: 26 Jan 2017
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
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- published: 26 Jan 2017
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4:53
Word Sense Disambiguation
published: 08 Dec 2013
Word Sense Disambiguation
Word Sense Disambiguation
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- published: 08 Dec 2013
- views: 449
4:49
Word Sense Relations: Synonyms
This video illustrates the different types of synonyms and shows why some words cannot be ...
published: 04 Nov 2016
Word Sense Relations: Synonyms
Word Sense Relations: Synonyms
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20:07
Word Sense Disambiguation - Natural Language Processing | Michigan
published: 27 Mar 2016
Word Sense Disambiguation - Natural Language Processing | Michigan
Word Sense Disambiguation - Natural Language Processing | Michigan
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- published: 27 Mar 2016
- views: 111
46:40
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science...
published: 03 Jul 2012
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
Mod-01 Lec-29 Wordnet and Word Sense Disambiguation
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- published: 03 Jul 2012
- views: 3553
11:51
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
If you are interest on more free online course info, welcome to: http://opencourseonline.c...
published: 30 Apr 2012
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning
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- published: 30 Apr 2012
- views: 4001
8:16
Semantics: Sense and Reference (Deixis)
Here is a lesson explaining when sentences have sense and when they have reference.
Expl...
published: 21 Jun 2016
Semantics: Sense and Reference (Deixis)
Semantics: Sense and Reference (Deixis)
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- published: 21 Jun 2016
- views: 1986
11:58
10 words in English that don't make sense! Hmmm...
Do you ever wonder why we park a car in a "driveway" but drive on a "parkway"? Why do we h...
published: 06 Oct 2016
10 words in English that don't make sense! Hmmm...
10 words in English that don't make sense! Hmmm...
- Report rights infringement
- published: 06 Oct 2016
- views: 223073
23:55
Sense relations
This video lecture is a part of the course 'An Introduction to English Linguistics' at the...
published: 18 Aug 2013
Sense relations
Sense relations
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- published: 18 Aug 2013
- views: 4985
43:10
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
Natural Language Processing by Prof. Pushpak Bhattacharyya, Department of Computer science...
published: 03 Jul 2012
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
Mod-01 Lec-34 Word Sense Disambiguation: Supervised and Unsupervised methods
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- published: 03 Jul 2012
- views: 2050
4:20
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean? WORD-SENSE DI...
published: 26 Jan 2017
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
What is WORD-SENSE DISAMBIGUATION? What does WORD-SENSE DISAMBIGUATION mean?
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- published: 26 Jan 2017
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4:53
Word Sense Disambiguation
published: 08 Dec 2013
Word Sense Disambiguation
Word Sense Disambiguation
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- published: 08 Dec 2013
- views: 449
4:49
Word Sense Relations: Synonyms
This video illustrates the different types of synonyms and shows why some words cannot be ...
published: 04 Nov 2016
Word Sense Relations: Synonyms
Word Sense Relations: Synonyms
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- published: 04 Nov 2016
- views: 186
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1:04:36
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S...
published: 14 Oct 2016
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words
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- published: 14 Oct 2016
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1:04:36
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S...
published: 14 Oct 2016
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words
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1:04:36
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S...
published: 19 Jul 2015
Sensing Murder S02E06 Lost For Words
Sensing Murder S02E06 Lost For Words
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- published: 19 Jul 2015
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49:07
Natural Language Processing Lecture 32 Word Sense Disambiguation
published: 16 Apr 2015
Natural Language Processing Lecture 32 Word Sense Disambiguation
Natural Language Processing Lecture 32 Word Sense Disambiguation
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- published: 16 Apr 2015
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47:23
Natural Language Processing Lecture 30 Wordnet and Word Sense Disambiguationcontd…
published: 16 Apr 2015
Natural Language Processing Lecture 30 Wordnet and Word Sense Disambiguationcontd…
Natural Language Processing Lecture 30 Wordnet and Word Sense Disambiguationcontd…
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46:40
Natural Language Processing Lecture 29 Wordnet and Word Sense Disambiguation
published: 16 Apr 2015
Natural Language Processing Lecture 29 Wordnet and Word Sense Disambiguation
Natural Language Processing Lecture 29 Wordnet and Word Sense Disambiguation
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49:16
Natural Language Processing Lecture 31 Wordnet; Metonymy and Word Sense Disambiguation
published: 16 Apr 2015
Natural Language Processing Lecture 31 Wordnet; Metonymy and Word Sense Disambiguation
Natural Language Processing Lecture 31 Wordnet; Metonymy and Word Sense Disambiguation
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1:29:34
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguation)
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguati...
published: 22 Nov 2016
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguation)
Empirical Methods in NLP (Lecture 6: Lexical knowledge network and Word Sense Disambiguation)
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- published: 22 Nov 2016
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2:48:59
Sensing Murder S02E06 Lost For Words Full Episode
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S...
published: 08 Nov 2016
Sensing Murder S02E06 Lost For Words Full Episode
Sensing Murder S02E06 Lost For Words Full Episode
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2:38:09
Sensing Murder S02E06 Lost For Words Full Episode
Sensing Murder S02E06 Lost For Words Sensing Murder S02E06 Lost For Words Sensing Murder S...
published: 15 Oct 2016
Sensing Murder S02E06 Lost For Words Full Episode
Sensing Murder S02E06 Lost For Words Full Episode
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- published: 15 Oct 2016
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Sensing Murder S02E06 Lost For Words...
Sensing Murder S02E06 Lost For Words...
Sensing Murder S02E06 Lost For Words...
Natural Language Processing Lecture 32 Word Sense ...
Natural Language Processing Lecture 30 Wordnet and...
Natural Language Processing Lecture 29 Wordnet and...
Natural Language Processing Lecture 31 Wordnet; Me...
Empirical Methods in NLP (Lecture 6: Lexical knowl...
Sensing Murder S02E06 Lost For Words Full Episode...
Sensing Murder S02E06 Lost For Words Full Episode...
See more photos of word sense
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Lyrics list:lyrics
-
My War, Your Problem, Weerd Science
-
Methods 'N Test Tubes, Weerd Science
-
Joshua, They're Laughing At You, Weerd Science
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Ordinary Joe (WCH), Weerd Science
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In A City With No Name, Weerd Science
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How To Be A, Weerd Science
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Girl, Your Baby's Worm Food, Weerd Science
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Fuck You and Your Filthy A&R; Department, Weerd Science
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Conspiracy Theories Without Mel Gibson, Weerd Science
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Blueprint, Weerd Science
-
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My War, Your Problem
Every one of my lyrics when you hear it
it'll burn your face as sulfuric acid
If you're holdin' the microphone I suggest you pass it.
Hand it over quickly
Sickly's the only way I know how to drop it
Every time I kick it people look at me like my name's
Ripley's Believe it or Not
Got a wonderful time slot here at the Zero Hour
Been laughed at for rappin' ever since I was a little coward
By all the kids who towered over me
Overpowered me and beat the shit out of my face
Like it's the job clock in an hour
And how are we the ones who powered these machines
And we can't get nothin' done, we controlled by kings and queens
The unseen son, the one in the attic
Hope the dream don't come true
America, she loves you
Without us who would back up the groceries
Or price up the clothes that you normally don't see
On average joes, oh that's me
Little dirtbag rapper and glad to be
I like my hip-hop dropped in tip-top condition
I keep on spittin' but no one listens
I must drop fire, I can not wait for a fall
This is our only hope, this is a war
This is a war
*Every picture you see is a reflection of marketing
The targeting of certain audiences as only a major corporation could
It's simple: They feed you shit. Just stop eating it, genius.
Run up in the Universal Office and find Doug Morris
Pound him in his office, his life ain't real pretty
Like bitches that sing choruses
These forces are forcin' us to try to relate
In spite of what they lead you to believe in the first place
Can't move in the city 'cause it's packed so tight
Everybody up in my business, dissin' the lyrics I write
Dismissin' my raps off their shoulder like the never happened
Actin' so thuggish like they tough like Tinactin
It's rubbish, it's all bubble gum to me
Nobody bumpin' me stoppin' by your record company
I'ma flatten MC's with platinum CDs
You see these two fists? They each got MT
Tons of Budweiser, got balls of steel wire
Like a sidewalk and supposedly ya'll are keepin' it real
But mostly ya just provoke and poke at me
And hopefully you remember your jokes to me
I like my hip-hop dropped in tip-top condition
I keep on spittin' but no one listens
I must drop fire, I can not wait for a fall
This is our only hope, this is a war
This is a war
*If ??? rap in you was approved by tests you'd see it's got nothin' to do with you.
The real gangstas are old white men putting these records out.
Hip-hop? That's the last thing they give a fuck about.*
By any means necessary I'm buryin' advesary
Every vocal performance it's important to stary vary
If you wanna feed all then you got motorcall
And I'm on the line, we can meet at the grassy knoll at ten
Maybe rap was never hip-hop to them
Seems like it's just a cash crop to them
So don't claim you spit it proper then
This war must never end
I can no longer pretend to be down
If I die in a battle that's fine
I got a potion named Revolution number 9
I got a heart that beats for the art
This is hip-hop for the love
Not a 1 on the charts
I like my hip-hop dropped in tip-top condition
I keep on spittin' but no one listens
I must drop fire, I can not wait for a fall
This is our only hope, this is a war
This is a war
This is a war, this is a war
This is a war, this is a war
back
Ice block the size of Delaware about to break away from Antarctica as global temperatures rise, scientists warn
Edit The Independent 03 Jul 2017
Read more ....
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20 including journalists, retired HC judge paid through hawala to fuel Kashmir unrest
Edit One India 03 Jul 2017
The security forces along with the Intelligence Bureau have prepared a list of 20 persons including journalists and a retired High Court judge who have been fueling unrest in the Valley. The list of 20 was prepared with the ... ....
back
Germany No Longer "Friends" With U.S. In Merkel's Election Campaign
Edit WorldNews.com 03 Jul 2017
In the campaign program for the upcoming German election, Chancellor Angela Merkel's conservatives have stopped describing Germany and the U.S. as 'friends,' according to Reuters. The program from 2013 of Merel's Christian Democratic Union (CDU) and their Bavarian sister party, the Christian Social Union (CSU), called the United States as Germany's "most important friend" outside of Europe ... out of the Paris climate accord....
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'Your worst nightmare: a successful Donald Trump presidency'
Edit The Guardian 03 Jul 2017
Donald Trump. 'Your worst nightmare. a successful Donald Trump presidency' ... But then came Donald Trump ... “We will never use those words on you, that’s for sure.” ... Indian prime minister Narendra Modi, for example, thanked Trump for “having spent so much time with me, for having spoken such kind words about me and my country … In this journey of India-America relations, I think I would like to thank you for providing great leadership.” ... 1.02....
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Thousands Of Foreign Workers Flee Thailand Over New Strict Labor Laws
Edit WorldNews.com 03 Jul 2017
Close to 60,000 workers have left Thailand between June 23 and 28 after new labor regulations from the military government ignited fear in the migrant community, with immigration officials saying the numbers have risen since then, according to Al Jazeera. "They were of all nationalities, but the biggest group was from Myanmar," Deputy Commissioner Pornchai Kuntee told Reuters news agency. "They are probably very scared." ... ....
Vocab Tunes Introduces 3 Amazing Products to Improve Vocabulary
Edit Community news 03 Jul 2017
Online learning platform Vocab Tunes has announced the availability of its reading programs—root word based products for children between the ages of 5 to 14. Comprising songs and root word recognition, these programs will help kids improve English scores ... The report revealed that in the past 50 years there has been a lack of knowledge related to English vocab words among school kids ... Vocab Tunes Root Words K-2 CD included....
BC-AP Entertainment Digest,2nd Ld-Writethru
Edit Reflector 03 Jul 2017
If you have questions, please email Anthony McCartney at amccartney@ap.org ... MONDAY, JULY 3 ... leader ... By Nasser Karimi ... 370 words, photos ... 780 words, photos ... 125 words, photos ... 130 words, photo ... 125 words, photo ... 120 words, photo ... 120 words, photos ... 250 words, photo ... 685 words, photos ... 725 words, photos ... 110 words ... 760 words, photo, video ... 500 words, photos, video ... 750 words, photos ... 830 words, photos ... 650 words by 5 p.m., photos ... 215 words ... 226 words ... ....
Reuters U.S. Sports Schedule at 2:45 PM ET on Monday, July 3
Edit DNA India 03 Jul 2017
(BBO-BLUEJAYS-CUBS-NEWS-MONTERO-TRADE, moved, The Sports Xchange, 328 words) ... ET game, The Sports Xchange, by David Driver, 700 words) ... ET, by The Sports Xchange, 400 words) ... ET, by The Sports Xchange, 400 words) ... (FBN-STARS-NEWS-RADULOV, moved, The Sports Xchange, 350 words) ... ET, The Sports Xchange, 575 words) ... (FBN-NOTEBOOK, The Sports Xchange, 500 words) ... (BKN-CAVALIERS-NEWS-BILLUPS, moved, The Sports Xchange, 397 words)....
77-887 Exam Dumps - Pass 77-887 Exam Easily with Latest Dumps
Edit Community news 03 Jul 2017
The Microsoft 77-887 examination fee is way too high for the students if they want to get a microsoft Word 2010 Expert Microsoft Office Specialist ... There are few things about Microsoft Word 2010 Expert which are to be kept in mind for achieving success in 77-887 ... Prepare and Clear Microsoft Word 2010 Expert with Practice Test Software ... Buy our product and get assured success in Microsoft Word 2010 Expert 77-887....
BC-AP Entertainment Digest
Edit Rocky Mount Telegram 03 Jul 2017
If you have questions, please email Anthony McCartney at amccartney@ap.org. Expanded AP content, beyond what appears here, can be obtained from http.//apexchange.com ... MONDAY, JULY 3 ... By Jake Pearson. SENT. 780 words, photos ... SENT. 125 words, photos ... SENT. 120 words, photos ... 685 words, photos ... 725 words, photos ... 110 words ... 760 words, photo, video ... 500 words, photos ... 750 words, photos ... 650 words by 1 p.m., photos ... 650 words by 5 p.m., photos ... 300 words....
Shah Rukh Khan thinks the context of Jab Harry Met Sejal is not objectionable; heard that Pahlaj Nihalani?
Edit Yahoo Daily News 03 Jul 2017
Ever since a news channel found 1 lakh votes to pass the word intercourse in Jab Harry Met Sejal, everybody has been in a happy daze. You all might have seen the video where the CBFC chairman Pahlaj Nihalani was questioned by a journalist to respond over the fact that the stipulated number of people did vote to let the word intercourse pass....
WORLD NEWS SCHEDULE AT 1400 GMT/1000 AM ET @ 7/3/2017 7:56:50 PM
Edit DNA India 03 Jul 2017
(GULF-QATAR/ (UPDATE 2), moved, by Noah Browning and Tom Finn, 619 words) ... (USA-TRUMP/ASIA (UPDATE 5, PIX,TV), moved, by Jeff Mason, 732 words) ... (USA-SOUTHCHINASEA/NAVY (UPDATE 4), moved, 595 words) ... (GERMANY-CRASH/ (UPDATE 4, TV, PIX), moved, 200 words) ... (FRANCE-SHOOTING/ (UPDATE 1), moved, 220 words) ... (FRANCE-ELECTION/NEWCOMER (FEATURE, PICTURE, TV), moved, by Ingrid Melander, 1,050 words) ... (MIDEAST-CRISIS/IRAQ-BLAST, moved, 125 words)....
Parents, take note: Picture books may not help your child learn more words
Edit Hindustan Times 03 Jul 2017
Children may love to see pictures on their storybooks, but having more illustrations than one on a page could result in poorer word learning among pre-schoolers, new research has found ... This has a dramatic impact on how well they learn new words from stories,” said study co-author Zoe Flack from University of Sussex in Britain....
AP-NC--North Carolina News Coverage Advisory 8:30 am, NC
Edit Rocky Mount Telegram 03 Jul 2017
Editors.. Assignment Editors.. Photo Editors.. Good morning! Here’s a look at how AP’s general news coverage is shaping up today in North Carolina. Questions about today’s coverage plans are welcome, and should be directed to interim Carolinas News Editor Jeffrey Collins at 803-603-8675 or at jscollins@ap.org. Jack Jones is on the desk, followed by Skip Foreman at 2 p.m ... SENT. 740 words ... 130 words ... 130 words ... 130 words ... 130 words ... 130 words....
My crash course in aphasia, the debilitating loss of the ability to talk
Edit The Guardian 03 Jul 2017
I had never heard the word “aphasia” and didn’t know what it was until I came round from brain surgery and found that I was unable to speak ... By the evening, I had recovered a few words ... The words you say automatically are often the first ones to come back; sometimes people can swear or sing before they can say their name ... Weird things were happening to my senses ... Other words started to come back – but not always the right ones....
Reuters Sports Schedule at 0001 GMT on Monday, July 3
Edit DNA India 03 Jul 2017
(SOCCER-CONFEDERATIONS-CHL-GER/, moved, 400 words) ... (SOCCER-FIFA/WORLDCUP (INTERVIEW), 500 words, expect by 1200 GMT/8 AM ET, By Brian Homewood) ... (RUGBY-UNION-LIONS/ROWNTREE, expect by 0400 GMT, midnight ET, by Greg Stutchbury, 402 words) ... (GOLF-QUICKENLOANS/, moved, 334 words) ... (GOLF-WOMEN-PGACHAMP/, expect by 2300 GMT/7 PM ET, by Andrew Both, 400 words) ... (GOLF-SENIOROPEN/, expect by 0100 GMT/9 PM ET, 300 words)....
A menacing old man in black
Edit Journal Online 03 Jul 2017
And, taking into consideration the large number of reports I get on a regular basis, I don’t state those words lightly ... In Terry’s own uninterrupted words ... I was lost for words when she spoke up and said, ‘Linda I don’t think he was a person, I think that old man was an alien.’ ... In trying to escape his words and his terrible messages to me, I began drinking heavily at night until I could find some peace in sleep....
Angela Merkel’s Party No Longer Considers the U.S. a “Friend”
Edit Slate 03 Jul 2017
German Chancellor Angela Merkel presented the conservative Christian Democratic Union (CDU) election manifesto on Monday and amid talk of tax cuts and a boost in security, there was a slight change in wording ... That was not the only change in the wording that reveals a shift in relations with Washington....
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