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I am looking for a source of nouns, adverbs, adjectives, and verbs in several languages.

I'd like the lists to already be split apart, and not have to go through the OED (and non-English equivalents) by hand re-creating said lists.

I don't really care about definitions, and I understand some words can be multiple parts of speech - that's fine - words like "many" could be a noun or adjective, and can appear in both lists.

Does anyone here know of such a source? If not, might someone be able to point me in the right direction?

I'm ok with the format being any of the following (or similar if folks have ideas):

  • csv: <word>, noun (y/n), verb (y/n), adverb (y/n), adjective (y/n)
  • plaintext files like "nouns", "verbs", etc
  • a mysql table
  • etc
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up vote 8 down vote accepted
+150

I have used WordNet from Princeton University for some projects. This is a lexical database in English. Global WordNet is an extension of the project trying to do the same for all languages.

You might also be interested in related projects at http://wordnet.princeton.edu/wordnet/related-projects/

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this looks really promising, thanks! – warren Apr 5 '10 at 2:22
    
WordNet is the way to go. All the top researchers use this. – mechko Apr 5 '10 at 16:41

This may not help at all, I don't know. But MediaWiki has an api for listing all pages belonging to a certain category. You could try using it on Wiktionary.org.

Notes:

  • Each query only returns 500 results. However, at the end, it also specifies a parameter to use in another query to get the next 500 results.
  • It includes everything in the specified category, even other sub-categories.
  • Results seem to be in alphabetical order, though everything starting with a capital letter comes before anything in lower case.

Examples:

Hope this helps, it's what I could come up with.

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I will second @teknikqa's suggestion of wordnet, but I would suggest you check out their APIs;

STORYTIME: I had an AI course that had a language analysis part; I used the wordnet's perl API's to automatically lookup the top three definition types, and classify the phrasing from that in near-realtime END OF STORYTIME

There are API's out there for Lots of languages

FYI: The project got an A+

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