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. |
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,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,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. |