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What is word sense disambiguation good for?

What is word sense disambiguation good for?. Adam Kilgarriff. The goal of WSD research is usually taken to be disambiguation between senses given in a dictionary, thesaurus or similar. senses. Word senses are a response to constraints imposed by: tradition the printed page compactness

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What is word sense disambiguation good for?

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  1. What is word sense disambiguation good for? Adam Kilgarriff

  2. The goal of WSD research is usually taken to be disambiguation between senses given in a dictionary, thesaurus or similar. senses

  3. Word senses are a response to constraints imposed by: • tradition • the printed page • compactness • a single, simple method of access • resolving disputes about what a word does and does not mean

  4. A dictionary must draw a line around the meaning.

  5. meaning

  6. meaning

  7. For reference: I don't believe in word senses (Kilgarriff, 1997)

  8. WSD application domains: • Information Retreival • Machine Translation • Parsing • Lexicography • Language Understanding

  9. IR Work Conclusion Compared Results Krovetz and Croft (1992) a perfect WSD program would improve performance by 2%. WS-ambiguity causes only limited degradation of IR performance IR performance „with ambiguity“ and „without ambiguity“ introducing extra ambiguity did little to degrade performance the performance of [IR] systems is insensitive to ambiguity but very sensitive to erroneous disambiguation pseudoword (banana-kalashnikov) pretending to be a single word with 2 meanings Sanderson (1994) system performance with the disambiguation module improved by up to 4.3% 4% is a significant improvement Schütze (1997) sensediscrimination

  10. MT • Two variants of ambiguity: • monolingual ambiguity • translational ambiguity No recent WSD work is employed in MT systems

  11. Parsing Consider a case of syntactic ambiguity (PP attachment): 1 I love baking cakes with friends. 2 I love baking cakes with butter icing. Lexical information can resolve many syntactic ambiguities without being sense-disambiguated.

  12. This good-for-nothing WSD Does WS ambiguity cause problems for NLP applications? IR: yes, to some moderate degree. Problems can substantially be overcome by using longer queries. MT: yes. Huge problem. Addressed to date by lots and lots of selection restrictions. Parsing: not known. Lexicography: yes, WSD would be of benefit. NLU: not much. NLU applications are mostly domain specic, and have some sort of domain model.

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