Difference between revisions of "Word sense disambiguation"

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Word sense disambiguation (WSD) is the ability of software to distinguish what sense of a word is being used in a textual context. In modern WSD systems, the senses are typically taken from some specified dictionary. In earlier systems the senses were more typically generic senses selected by the originators of the system. These days WordNet is the usual dictionary in question. WSD has been investigated in computational linguistics as a specific task for well over 40 years, though the acronym is newer. The SENSEVAL conferences have attempted to put Word Sense Disambiguation on an empirically measurable basis by hosting evaluations in which a given corpus of tagged word senses are created using WordNet's senses and participants attempt to recognize those senses after tuning their systems with a corpus of training data.
 
Word sense disambiguation (WSD) is the ability of software to distinguish what sense of a word is being used in a textual context. In modern WSD systems, the senses are typically taken from some specified dictionary. In earlier systems the senses were more typically generic senses selected by the originators of the system. These days WordNet is the usual dictionary in question. WSD has been investigated in computational linguistics as a specific task for well over 40 years, though the acronym is newer. The SENSEVAL conferences have attempted to put Word Sense Disambiguation on an empirically measurable basis by hosting evaluations in which a given corpus of tagged word senses are created using WordNet's senses and participants attempt to recognize those senses after tuning their systems with a corpus of training data.
  
Word Sense Disambiguation has several debates within the field as to whether the senses offered in existing dictionaries are adequate to distinguish the subtle meanings used in text contexts and how to evaluate the overall performance of a WSD system. For example, does it make sense to describe an overall percentage accuracy to a WSD system or does evaluation require specific comparison of system performance on a word by word basis.  
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Word Sense Disambiguation has several debates within the field as to whether the senses offered in existing dictionaries are adequate to distinguish the subtle meanings used in text contexts and how to evaluate the overall performance of a WSD system. For example, does it make sense to describe an overall percentage accuracy for a WSD system or does evaluation require specific comparison of system performance on a word by word basis.  
  
 
Among the earliest efforts at word sense disambiguation was the work of Kelly & Stone (Ref needed) who published a book explicitly listing their rules for disambiguation of word senses.
 
Among the earliest efforts at word sense disambiguation was the work of Kelly & Stone (Ref needed) who published a book explicitly listing their rules for disambiguation of word senses.

Revision as of 09:38, 7 November 2006

Word Sense Disambiguation

Word sense disambiguation (WSD) is the ability of software to distinguish what sense of a word is being used in a textual context. In modern WSD systems, the senses are typically taken from some specified dictionary. In earlier systems the senses were more typically generic senses selected by the originators of the system. These days WordNet is the usual dictionary in question. WSD has been investigated in computational linguistics as a specific task for well over 40 years, though the acronym is newer. The SENSEVAL conferences have attempted to put Word Sense Disambiguation on an empirically measurable basis by hosting evaluations in which a given corpus of tagged word senses are created using WordNet's senses and participants attempt to recognize those senses after tuning their systems with a corpus of training data.

Word Sense Disambiguation has several debates within the field as to whether the senses offered in existing dictionaries are adequate to distinguish the subtle meanings used in text contexts and how to evaluate the overall performance of a WSD system. For example, does it make sense to describe an overall percentage accuracy for a WSD system or does evaluation require specific comparison of system performance on a word by word basis.

Among the earliest efforts at word sense disambiguation was the work of Kelly & Stone (Ref needed) who published a book explicitly listing their rules for disambiguation of word senses.