Converting from treebank tags to wordnet-compatible tags in Java?

Some more information about what you're wanting to do with WordNet associations might be helpful, but my first guess is that you want to discard parts-of-speech which don't map cleanly to the WordNet categories.

Some more information about what you're wanting to do with WordNet associations might be helpful, but my first guess is that you want to discard parts-of-speech which don't map cleanly to the WordNet categories. For example, consider DT (determiner). Are you hoping to get a relationship between, say, 'the' and 'an' from WordNet?

Similarly, there might be useful relationships in WordNet for PP (prepositions), but I suspect you're much more likely to find helpful relationships between different nouns or verbs than between closed-class words. My recommendation is to start by mapping each of the TreeBank part-of-speech tags to one of the WordNet classes, or to 'null' for those parts-of-speech that don't have obvious mappings (you could probably find such a mapping somewhere, but with only 36 tags, it might be just as easy to do yourself). For closed-class words, you might decide to use another source of relationship metadata, but that will probably depend on the end-goal of your application.

Extracting synsets from WordNet isn't usually an end-goal. What sort of mapping would you like to find for 'an', for example? I'm not anything close to an expert on WordNet, but I wouldn't expect to find synonyms of antonyms for 'an', 'the', 'of', etc. The concept of synonym and antonym doesn't make much sense for closed-class words.

– AaronD Apr 18 at 20:18 extracting synsets for text summarization is my application.. – Navin Israni Apr 19 at 3:31.

I cant really gove you an answer,but what I can give you is a way to a solution, that is you have to find the anglde that you relate to or peaks your interest. A good paper is one that people get drawn into because it reaches them ln some way.As for me WW11 to me, I think of the holocaust and the effect it had on the survivors, their families and those who stood by and did nothing until it was too late.