Graph-Based Taxonomic Semantic Class Labeling

Abstract

We present a graph-based method for the lexical task of labeling senses of polysemous lexemes. The labeling task aims at generalizing sense features of a lexical item in a corpus using more abstract concepts. In this method, a coordination dependency-based lexical graph is first constructed with clusters of conceptually associated lexemes representing related senses and conceptual domains of a source lexeme. The label abstraction is based on the syntactic patterns of the x is_a y dependency relation. For each sense cluster, an additional lexical graph is constructed by extracting label candidates from a corpus and selecting the most prominent is_a collocates in the constructed label graph. The obtained label lexemes represent the sense abstraction of the cluster of conceptually associated lexemes. In a similar graph-based procedure, the semantic class representation is validated by constructing a WordNet hypernym relation graph. These additional labels indicate the most appropriate hypernym category of a lexical sense community. The proposed labeling method extracts hierarchically abstract conceptual content and the sense semantic features of the polysemous source lexeme, which can facilitate lexical understanding and build corpus-based taxonomies.

Keywords

• lexical graph analysis
• corpus
• syntactic–semantic dependency
• word sense
• hypernym
• knowledge representation and reasoning