Bridging the Gap between Dictionary and Thesaurus

This paper presents an algorithm to integrate different lexical resources, through which we hope to overcome the individual inadequacy of the resources, and thus obtain some enriched lexical semantic information for applications such as word sense disambiguation. We used WordNet as a mediator between a conventional dictionary and a thesaurus. Preliminary results support our hypothesised structural relationship, which enables the integration, of the resources. These results also suggest that we can con> bine the resources to achieve an overall balanced degree of sense discrimination. 1 I n t r o d u c t i o n It is generally accepted that applications such as word sense disambiguation (WSD), machine translation (MT) and information retrieval (Ill.), require a wide range of resources to supply the necessary lexical semantic information. For instance, Calzolari (1988) proposed a lexieal database in Italian which has the features of both a dictionary and a thesaurus; and Klavans and Tzoukermann (1995) tried to build a fuller bilingual lexicon by enhancing machine-readable dictionaries with large corpora. Among the a t t empts to enrich lexical information, many have been directed to the analysis of dictionary definitions and the t ransformation of the implicit information to explicit knowledge bases for computat ional purposes (Amsler, 1981; Calzolari, 1984; Chodorow et al., 1985; Markowitz et al., 1986; Klavans et al., 1990; Vossen and Copestake, 1993). Nonethdess, dictionaries are also infamous of their non-standardised sense granularity, and the taxonomies obtained from definitions are inevitably ad hoe. It would therefore be a good idea if we can unify our lexical semantic knowledge by some existing, and widely exploited, classifications such as the system in Roget 's Thesaurus (Roget, 1852), which has remained intact for years and has been used in WSD (Yarowsky, 1992). While the objective is to integrate ditferent lexical resources, the problem is: how do we recoi> cile the rich but variable information in dictionary senses with the cruder but more stable taxonomies like those in thesauri7 This work is intended to fill this gap. We use WordNet as a mediator in the process, in the following, we will outline an algorithm to map word senses in a dictionary to semantic classes in some established classitication scheme. 2 I n t e r r e l a t e d n e s s o f t h e R e s o u r c e s Tlle three lexical resources used in this work are the 1987 revision of Roget 's Thesaurus (ROGET) (Kirkpatrick, 1987), the Longman Dictionary of Contemporary English (I ,DOCE) (Procter, 1978) and WordNet 1.5 (WN) (Miller et al., 1993). Figure 1 shows how word senses are organised in them. As we have mentioned, instead of directly mapping an I ,DOCE definition to a R O G E T class, we bridge the gap with WN, as indicated by the arrows in t;|Ie figure. Such a route is made feasible by linking the structures in common among the resources. Words are organised in alphabetical order in LDOCE, as in other conw;ntioual dictionaries. The senses are listed after each entry, in the form of text definitions. WN groups words into sets of synonyms (%ynsets"), with an optional textual gloss. These synsets form the nodes of a taxonomic hierarchy. in I1.OGET, each semantic class comes with a nuinber, under which words are first assorted by part of speech and then grouped into paragraphs according to the conw.'yed idea. Let us refer to Figure 1 and s tar t from word x2 in WN synset X. Since words expressing every aspect of an idea are grouped together in II.()GET, we can therefore expect to find not only words in synset X, but also those in the coordinate WN synsets (i.e. M and P, with words ml , m2, pl , P2, etc.) and the superordinate WN synsets (i.e. C and A, with words cj, c2, etc.) in the same R O G E T paragraph. In other words, the thesaurus class to which x2 belongs should include roughly X U M U I ' U C U A. Meanwhile, the LDOCE definition corresponding to the sense of synset X (denoted by Dx) is expected to be sinfilar to the textual gloss of synset X (denoted by GI(X)). In addition, given that it is not unusual for