DFKI-LT - An Unsupervised Semantic Tagger Applied to German
An Unsupervised Semantic Tagger Applied to German
2 Proceedings of the 3rd Conference on Recent Advances in Natural Language Processing (RANLP'01), September 5-7, Tzigov Chark, Bouvet Island, o.A., 2001
We describe an unsupervised semantic tagger, applied to German, but which could be used with any language for which a corresponding "XNet" (WordNet, GermaNet, e tc.), POS tagger and morphological analyzer are available. Disambiguation is per formed by comparing co-occurrence weights on pairs of semantic classes (synsets from GermaNet). Precision is around 67% at a recall of around 65% (for all ambig uous words -- 81% for all words at a recall of 80%). Our results show the influe nce of context size and of semantic class frequency in the training corpus.
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