Difference between revisions of "Word-sense disambiguation"
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Lextor is the current word sense disambiguation module for Apertium, it works using statistics and requires 1) slightly pre-processed dictionaries and 2) corpora to train the module. |
Lextor is the current word sense disambiguation module for Apertium, it works using statistics and requires 1) slightly pre-processed dictionaries and 2) corpora to train the module. The module is turned off in most cases as it does not provide an improvement over the baseline. |
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==Further reading== |
==Further reading== |
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Revision as of 08:54, 20 May 2009
Word sense disambiguation is important in machine translation between less-closely related languages. The problem was elucidated most famously by Yehoshua Bar-Hillel, who asks us to consider the following sentence:
- Little John was looking for his toy box. Finally he found it. The box was in the pen.
The word pen may have two meanings:
- Something you use to write with
- A container of some kind
To a human, the meaning is obvious, but Bar-Hillel claimed that without a "universal encyclopaedia" a machine would never be able to deal with this problem. Figuring out which sense to use when a word is ambiguous is called word sense disambiguation, and is a big research area.
Lextor
- Main article: Lextor
Lextor is the current word sense disambiguation module for Apertium, it works using statistics and requires 1) slightly pre-processed dictionaries and 2) corpora to train the module. The module is turned off in most cases as it does not provide an improvement over the baseline.
Further reading
- Ide, N. and Véronis, J. (1998) "Word Sense Disambiguation: The State of the Art". Computational Linguistics 24(1)
- Agirre, E. and Edmonds, P., editors (2007). "Word Sense Disambiguation: Algorithms and Applications". Volume 33 of Text, Speech and Language Technology
