Difference between revisions of "Word-sense disambiguation"

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{{main|Lextor}}
{{main|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.
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.'''


==See also==
==See also==

Revision as of 14:44, 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:

  1. Something you use to write with
  2. 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.

See also

Further reading

  • Agirre, E. and Edmonds, P., editors (2007). "Word Sense Disambiguation: Algorithms and Applications". Volume 33 of Text, Speech and Language Technology