<?xml version="1.0" standalone="yes"?>
<Paper uid="C94-2122">
  <Title>Automatic Recognition of Verbal Polysemy</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> '\]?here has 1)een quite a h)t of research concerned with automatic clustering of semantically similar words or automatic recognition of colloc~rtions among them from eorl)ort~ \[Church, 1OVl\], \[Hindle, 1991\], \[Smadja, 1991\]. Most of this work is based on similarity measures derived fl'om the distrilmtion of woMs in corpora. However, the Nets that a single word does have more than one meaning and that the distribution of a word in a corpus is a mixture of usages of different meanings of the same word often hamper such atteml~ts.</Paragraph>
    <Paragraph position="1"> The meaning of a word depends on the domain in which it is used; the sitme word c'an be use(l differently in different dolnains. It is also often the ease theft a word which is l/olysemous in general is not l)olysemous in a r(,strieted subject domain. In general, restriction of tllc subject domain makes the t)roblenl of 1)olysemy less l)rol)lematie. However, even in texts fronl a restricted domain such as Wall Street Journal l, one eneount.ers quite a large nulnber of l)olyselnous words, in particular, unlike nouns, verbs are often i/olys(mwus ev(,n in a restricted subject domain.</Paragraph>
    <Paragraph position="2"> Because polysemous verbs are usually also high-frequency verbs, their treal:ment is crucial ill actual applications. Furthermore, beeause of their highfrequen(:y, polysemous verbs tend to have a harmflfl inth,ence on the senlantic ehtstering of l/ollns, \])eeallSO semantic clustering of nollns is usually 1)eribrmed based on th(.ir eollo('ational 1)ehaviour with verbs.</Paragraph>
    <Paragraph position="3"> * I.'UKUMOTO i.~ now at Department of Ele(:trical Engineering mM (~omputcr Sciencc, Faculty of EngineerilJg, Yamanashi UaivcrMty. E-mail fukumoto~skyc.esi,yamalmshi.ac.jp t Wall Street ,lo'~tr'nal was prepared by ACi,(Associalkm for (~omputational IAt~gMstics' Data Collection Initi~ttivu) in \[99l. Although polysemy is said to be widespread in language, the definition of polysemy is highly subjective.</Paragraph>
    <Paragraph position="4"> Polysemy can only be recognised by hunmn intuition and different linguists often identify a different number of senses in the same word. In this paper, we first give a definition of polysemy fl'om the viewpoint of clustering, and propose an overlapping clustering method which automatically reeognises polysemous words. The results of experiments are also given to demonstrate the effectiveness of our method.</Paragraph>
  </Section>
class="xml-element"></Paper>