Constructing Semantic Space Models from Parsed Corpora

نویسندگان

  • Sebastian Padó
  • Mirella Lapata
چکیده

Traditional vector-based models use word co-occurrence counts from large corpora to represent lexical meaning. In this paper we present a novel approach for constructing semantic spaces that takes syntactic relations into account. We introduce a formalisation for this class of models and evaluate their adequacy on two modelling tasks: semantic priming and automatic discrimination of lexical relations.

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تاریخ انتشار 2003