| tech,7-1-C04-1112,bq | </term> . In this paper , we present a <term> | corpus-based supervised word sense disambiguation ( WSD ) system | </term> for <term> Dutch </term> which combines | #5986 In this paper, we present acorpus-based supervised word sense disambiguation ( WSD ) system for Dutch which combines statistical classification (maximum entropy) with linguistic information. |
| other,17-1-C04-1112,bq | disambiguation ( WSD ) system </term> for <term> | Dutch | </term> which combines <term> statistical classification | #5996 In this paper, we present a corpus-based supervised word sense disambiguation (WSD) system forDutch which combines statistical classification (maximum entropy) with linguistic information. |
| tech,20-1-C04-1112,bq | for <term> Dutch </term> which combines <term> | statistical classification ( maximum entropy ) | </term> with <term> linguistic information </term> | #5999 In this paper, we present a corpus-based supervised word sense disambiguation (WSD) system for Dutch which combinesstatistical classification ( maximum entropy ) with linguistic information. |
| other,27-1-C04-1112,bq | classification ( maximum entropy ) </term> with <term> | linguistic information | </term> . Instead of building individual <term> | #6006 In this paper, we present a corpus-based supervised word sense disambiguation (WSD) system for Dutch which combines statistical classification (maximum entropy) withlinguistic information. |
| tech,4-2-C04-1112,bq | </term> . Instead of building individual <term> | classifiers | </term> per <term> ambiguous wordform </term> | #6013 Instead of building individualclassifiers per ambiguous wordform, we introduce a lemma-based approach. |
| 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 perambiguous 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 alemma-based approach. |
| other,15-3-C04-1112,bq | all <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 anambiguous word in one classifier, therefore augmenting the training material available to the algorithm. |
| tech,19-3-C04-1112,bq | an <term> ambiguous word </term> in one <term> | classifier | </term> , therefore augmenting the <term> training | #6043 The advantage of this novel method is that it clusters all inflected forms of an ambiguous word in oneclassifier, therefore augmenting the training material available to the algorithm. |
| lr,24-3-C04-1112,bq | classifier </term> , therefore augmenting the <term> | training material | </term> available to the algorithm . Testing | #6048 The advantage of this novel method is that it clusters all inflected forms of an ambiguous word in one classifier, therefore augmenting thetraining 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 thelemma-based model on the Dutch SENSEVAL-2 test data, we achieve a significant increase in accuracy over the wordform model. |
| lr-prod,6-4-C04-1112,bq | <term> lemma-based model </term> on the <term> | Dutch SENSEVAL-2 test data | </term> , we achieve a significant increase | #6061 Testing the lemma-based model on theDutch SENSEVAL-2 test data, we achieve a significant increase in accuracy over the wordform model. |
| measure(ment),17-4-C04-1112,bq | achieve a significant increase in <term> | accuracy | </term> over the <term> wordform model </term> | #6072 Testing the lemma-based model on the Dutch SENSEVAL-2 test data, we achieve a significant increase inaccuracy over the wordform model. |
| tech,20-4-C04-1112,bq | increase in <term> accuracy </term> over the <term> | wordform model | </term> . Also , the <term> WSD system based | #6075 Testing the lemma-based model on the Dutch SENSEVAL-2 test data, we achieve a significant increase in accuracy over thewordform model. |
| tech,3-5-C04-1112,bq | <term> wordform model </term> . Also , the <term> | WSD system based on lemmas | </term> is smaller and more robust . We present | #6081 Also, theWSD system based on lemmas is smaller and more robust. |
