Automatic Synonymy Extraction : A Comparison of Syntactic Context Models
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Publication date
2008-11
Authors
Heylen, Kris
Peirsman, Yves
Geeraerts, Dirk
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Abstract
Distributional models of lexical semantics identify semantically similar words through contextual
similarity. Previous studies have shown that syntactic contexts are especially good
at finding (near) synonyms. In this paper, we compare models based on eight different syntactic
dependency relations and we evaluate their separate and combined performance on a
test set of Dutch nouns. Firstly, we analyze to what extent their results overlap. Secondly,
we assess the overall performance of the models by looking at the average similarity of the
words they return. And thirdly, we compare the specific semantic relations retrieved by the
models. The analyses show that although models based on the subject and object relation
give the most consistent results, it is the model based on adjective modification that gives
the best results. It even outperforms the combined model at finding true synonyms.