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He did it for one word. Bad article title.



It was actually a method of using wikipedia to build your corpus for any ambiguous word to automatically build some word sense disambiguation in your application. One word was just a simple example of using that data.


- The article does not add anything new. Using Wikipedia for word sense disambiguation has been a hot topic for some years. [1]

- The article title implies that this is somehow a spectacular finding. Doing word sense disambiguation for one word is not that interesting, and there is no comparison with existing methods to show that this is actually a high score. I suspect that it is not that spectacular, since 'Apple' is relatively easy to disambiguate using a few context words.

[1] E.g. see:

- Using Wikipedia for Automatic Word Sense Disambiguation, R. Mihalcea, 2007, for a discussion of using Wikipedia to train a word sense disambiguator.

- Integrating multiple knowledge sources to disambiguate word sense: An exemplar-based approach, H.T. Ng and H.B. Lee, 1996, provide a good overview of types of features that can be used in disambiguation. They use features that go beyond simple 'bag of word' and 'bag of n-gram' features, e.g. by using syntactical patterns.

There is a whole lot more research of course, but just to show two examples that describe far more sophisticated approaches.




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