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<Paper uid="W06-3504">
  <Title>Increasing the coverage of a domain independent dialogue lexicon with VERBNET</Title>
  <Section position="4" start_page="0" end_page="25" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> This paper explores how different lexicons can be integrated with the goal of extending coverage of a deep parser and semantic interpreter. Lexical semantic databases (Kipper et al., 2000; Johnson and Fillmore, 2000; Dorr, 1997) use a frame-based model of lexical semantics. Each database groups words in classes where predicative words and their arguments are described. The classes are generally organised in an inheritance structure. Each such database can be used, among other things, to perform semantic interpretation. However, their actual structures are quite different, reflecting different underlying methodological approaches to lexical description, and this results in representation that are not directly compatible. Since no such database has full coverage of English, it is worth combining them in order to get a lexicon with better coverage and a unified representation for English.</Paragraph>
    <Paragraph position="1"> We explore the issues related to merging verb descriptions from two lexical databases, which have both syntactic and semantic incompatibilities, and compare two techniques for aligning semantic classes and the syntax-semantics mappings between them. The resulting lexicon is to be used in precise interpretation tasks, so its consistency and accuracy are a high priority. Thus, though it is possible to generate lexical entries automatically (Kwon and Hovy, 2006; Swift, 2005), we use a semi-automatic method in which an expert hand-checks the automatically generated entries before adding them to the lexicon.</Paragraph>
    <Paragraph position="2"> Therefore, our goal is to maximise the number of new useful entries added to the lexicon while minimising the number of entries that are discarded or hand-edited.</Paragraph>
    <Paragraph position="3"> We take the mapping between the TRIPS lexicon and the VERBNET lexical database as a case study for our experiment. The TRIPS lexicon is used together with a parser to provide a natural language understanding component for several dialogue applications in different domains. It outputs highly detailed semantic representations suitable for complex dialogue tasks such as problem-solving and tutoring dialogue, inter alia. An essential feature of TRIPS is the integration of a detailed lexical semantic representation, semantic classes and theta role assignments in the parsing process.</Paragraph>
    <Paragraph position="4"> Semantic types and role labelling are helpful in both deep (Tetreault, 2005) and shallow interpretation tasks (Narayanan and Harabagiu, 2004). TRIPS provides a convenient test case because its grammar is already equipped with the formal devices required to build up a frame-based semantic representation including this information.1  We chose VERBNET to extend the TRIPS lexicon because it includes a detailed syntax-semantic mappings, thus providing a more convenient interface to the syntactic component of the grammar than lexicons where this connection is left unclear, such as FRAMENET. However the methods described here are designed to be reusable for merging other lexical databases, in particular we intend to experiment with FRAMENET in the near future.</Paragraph>
    <Paragraph position="5"> The plan of the paper is as follows: we first describe the target lexicon (Section 2) and the source lexicon (Section 3) for our experiment before describing the methodology for integration (Section 4). We finally present an evaluation of the techniques in Section 5.</Paragraph>
  </Section>
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