Author:

Keywords:

computational linguistics, lexical semantics

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.