Automatic Recognition of Verbal Polysemy

Polysemy is one of the major causes of difficulties in selnantic clustering of words in a corpus. In this paper, we first; give a definition of polysemy from the viewpoint of clustering and then, b~rsed on this definition, we propose a clustering method which reeognises verbal 1)olysemics from a textual corpus. The results of experiments denmnst ra te the effectiveness of the proI)osed method. 1 I n t r o d u c t i o n ']?here has 1)een quite a h)t of research concerned with automat ic clustering of semantically similar words or automat ic 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 distr i lmtion of woMs in corpora. However, the Nets tha t a single word does have more than one meaning and tha t the distr ibut ion of a word in a corpus is a mixture of usages of different meanings of the same word often hamper such atteml~ts. 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. Because polysemous verbs are usually also highfrequency 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. * 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 W a l l S t r e e t ,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. Polysemy can only be recognised by hunmn intuit ion and different linguists often identify a different number o f 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 demonst ra te the effectiveness of our method. 2 R e l a t e d Work Although there have been several a t tempts to extract semantically similar words from a, given corpus, few studies seriously deal with the problenl of 1)olysemy; of these, even fewer are based on real texts. The techniques developed by Zernik [Zernik, 1991] and Brown [Brown, 1991] seem to cope with the discrimination of polysemy and 1)e ll~Lse(l on real texts. Zernik used monolingual texts which consist of about 1 nfillion words tagged by 1)art-of-spee(:h. I~Iis method associates ca(-h word se.nse of a polysemous woM with a set of its co-occurring words. If a word has sew eral senses, then the word is assoeiated with several different sets of co-occurring words, each of which corresponds to one of the senses of the word. The linfitation of Zernik's method, however, is tha t it solely relies on human intuit ion for identifying different senses of a word, i.e. the human editor tlas to determine, by her /h is intuition, how many seilses a word has, and then identii~y the sets of co-occurring words (signat.lcres) tha t correspond to the different senses. Brown used bilingual texts, which consist of ]2 million words. The results of Brown's technique, when al)plied to a French-English nmchine transb~tion system, seems to show its eflbctiveness and validity. However, as he admits, the at)preach is linfited because it can only assign at most two senses to a word. More seriously, 1)olysemy is defined in terms of translation, i.e. only when a word is Lranslated into two different words in a target language, it is recogniscd as polysemous. The apllroach can bc used only when a large 1)aral lel corpus is awdhtble. Furthermore, individual senses thus identified (1(1 not neeessarily const i tute single semant ic units in the monolingual domain to which 1)lausible semantic prollertics (i.e. semantic rest;rictions,