Editing Word-sense disambiguation (section)

===Part-of-speech tagging===
In any real test, [[part-of-speech tagging]] and sense tagging have proven to be very closely related, with each potentially imposing constraints upon the other. The question whether these tasks should be kept together or decoupled is still not unanimously resolved, but recently scientists incline to test these things separately (e.g. in the Senseval/[[SemEval]] competitions parts of speech are provided as input for the text to disambiguate).

Both WSD and part-of-speech tagging involve disambiguating or tagging with words. However, algorithms used for one do not tend to work well for the other, mainly because the part of speech of a word is primarily determined by the immediately adjacent one to three words, whereas the sense of a word may be determined by words further away. The success rate for part-of-speech tagging algorithms is at present much higher than that for WSD, state-of-the art being around 96%<ref>{{Cite journal|last=Martinez|first=Angel R.|date=January 2012|title=Part-of-speech tagging: Part-of-speech tagging|url=http://doi.wiley.com/10.1002/wics.195|journal=Wiley Interdisciplinary Reviews: Computational Statistics|language=en|volume=4|issue=1|pages=107–113|doi=10.1002/wics.195|s2cid=62672734|access-date=2021-04-01|archive-date=2023-07-15|archive-url=https://web.archive.org/web/20230715100019/https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/wics.195|url-status=live}}</ref> accuracy or better, as compared to less than 75%{{Citation needed|date=March 2014}} accuracy in word sense disambiguation with [[supervised learning]]. These figures are typical for English, and may be very different from those for other languages.