Clustering in the Discovery of Semantic Frames

Rebecca Green, Rebecca Green, Rebecca Green, Rebecca Green

Abstract


This paper describes the use of clustering at three stages within a larger research effort to identify semantic frames used in English automatically. The first of two tasks within this effort has been the identification of sets of semantically related verb senses that invoke a common semantic frame. Within this task, clustering has been used both to build sets of verb senses with the potential of invoking a common semantic frame and then to merge sets with a high degree of overlap. The paper is organized as follows: Section 2 introduces frame semantics. Section 3 outlines the methodology used to identify sets of semantically related verb senses that invoke a common semantic frame, while section 4 presents the specific clustering algorithm used within that process. Section 5 discusses the use of this clustering algorithm for the identification of semantically related verbs in two machine-readable lexical resources: the machine-readable version of the Longman Dictionary of Contemporary English (LDOCE, 1978 edition) and WordNet, an online lexical database (http://www.cogsci.princeton.edu/-wn; version 1.7.1 has been used for the work reported here). Section 6 presents the use of clustering to merge overlapping sets of verb senses formed in previous steps. Section 7 discusses the results of these clusterings, paying particular attention to the effect of LDOCE's restricted defining vocabulary on the clustering process.

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DOI: http://dx.doi.org/10.7152/acro.v14i1.14109