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<Paper uid="W03-1808">
  <Title>Verb-Particle Constructions and Lexical Resources</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> In this paper we discuss verb-particle constructions (VPCs) in English and analyse some of the available sources of information about them for use in NLP systems. VPCs can range from idiosyncratic or semi-idiosyncratic combinations, such as get on (in e.g. Bill got on well with his new colleagues), to more regular ones, such as tear up (in e.g. In a rage she tore up the letter Jack gave her). However, examples of 'idiomatic' VPCs like get on, meaning to be on friendly terms with someone, where the meaning of the combination cannot be straightforwardly inferred from the meaning of the verb and the particle, fortunately seem to be a small minority (Side, 1990). Most cases seem to be more regular, with the particle compositionally adding a speci c meaning to the construction and following a productive pattern (e.g. in tear up, cut up and split up, where the verbs are semantically related and up adds a sense of completion the action of these verbs).</Paragraph>
    <Paragraph position="1"> VPCs have been the subject of a considerable amount of interest, and some investigation has been done on the subject of productive VPCs. For instance, even though the particle up occurs with a wide range of verbs, it only combines productively with some classes. Bame (1999) discusses two such cases: the resultative and the aspectual up. For example Kim carried the television up uses a resultative up and Kim ate the sandwich up an aspectual up. With the resultative up, the argument is affected (i.e., at the end of the action the television is up).</Paragraph>
    <Paragraph position="2"> In contrast, the aspectual or completive up suggests that the action is taken to some conclusion (i.e., the sandwich is totally consumed at the end of the action). null Fraser (1976) points out that semantic properties of verbs can affect their possibilities of combining with particles. Thus, semantic properties can in uence the patterns of verb-particle combinations that verbs follow. For example, in the case of bolt/cement/clam/glue/paste/nail all are semantically similar verbs where the objects speci ed by the verbs are used to join material and they can all combine with down. There is clearly a common semantic thread running through this list, so that a new verb that is semantically similar to them can also be reasonably assumed to combine with down. Indeed Side notes that frequently new VPCs are formed by analogy with existing ones, with often the verb being varied and the particle remaining (e.g. hang on, hold on and wait on).</Paragraph>
    <Paragraph position="3"> By identifying classes of verbs that follow patterns such as these in VPCs, we are able to maximise the use of the information contained in lexical resources. For instance, we can make use of regular patterns to productively generate VPCs from verbs already listed in a lexical resource, according to their verbal classes (e.g. the resultative combinations walk up/down/out/in/away/around/... from walk and the directional/locative particles up, down, out, in, away, around, ...). We consider how we can use productive patterns to extend the coverage of current lexical resources, in the next sections. We start by characterising VPCs, and investigating the coverage provided by some available electronic dictionaries, in section 3. We also discuss the use of corpora to extend the coverage provided by these dictionaries.</Paragraph>
    <Paragraph position="4"> After that we investigate how more productive combinations can be generated from a semantic classi cation of verbs such as Levin's (1993).</Paragraph>
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