| other,27-1-C04-1112,bq | classification ( maximum entropy ) </term> with <term> | linguistic information | </term> . Instead of building individual | #6006 In this paper, we present a corpus-based supervised word sense disambiguation (WSD) system for Dutch which combines statistical classification (maximum entropy) with linguistic information . |
| other,6-2-C04-1112,bq | individual <term> classifiers </term> per <term> | ambiguous wordform | </term> , we introduce a <term> lemma-based | #6015 Instead of building individual classifiers per ambiguous wordform , we introduce a lemma-based approach. |
| tech,12-2-C04-1112,bq | ambiguous wordform </term> , we introduce a <term> | lemma-based approach | </term> . The advantage of this novel method | #6021 Instead of building individual classifiers per ambiguous wordform, we introduce a lemma-based approach . |
| other,15-3-C04-1112,bq | <term> inflected forms </term> of an <term> | ambiguous word | </term> in one <term> classifier </term> , therefore | #6039 The advantage of this novel method is that it clusters all inflected forms of an ambiguous word in one classifier, therefore augmenting the training material available to the algorithm. |
| tech,2-4-C04-1112,bq | available to the algorithm . Testing the <term> | lemma-based model | </term> on the <term> Dutch SENSEVAL-2 test | #6057 Testing the lemma-based model on the Dutch SENSEVAL-2 test data, we achieve a significant increase in accuracy over the wordform model. |
