To what extent does case contribute to verb sense disambiguation?

To what extent does case contribute to verb sense disambiguation? FUJI1 Atsushi, INUI Kentaro, TOKUNAGA Takenobu and TANAKA Hozmni Det)artlnent of CoInl)utox Scien(:e Tokyo Institute of Technology 2-12-11 ()ookayama Meguroku ~[bkyo 152, JAPAN {fujii,inui,take,tanaka}@cs.titech.ac.jp Abstract Word sense disambugation has re- cently been utilized in corpus-based aI)- proaches, reflecting the growth in the number of nmehine readable texts. One (:ategory ()f al)l)roa(:hes disambiguates an input verb sense based on the similar- ity t)etween its governing (:its(; fillers and those in given examl)les. In this palter , we introdu<:c the degree of (:<mtriblltion of cast; to verb sells(', disambignation intt) this existing method, in this, greater di- versity of semanti(: range of case filler ex- amples will lead to that ease contributing to verb sense disambiguation more. We also report th(; result of a coml)arative ext)eriment, in which the t)erfornlance of disaml)igui~tion is iml)rt)ved t)y consider- ing this notion of semantic contribution. 1 Introduction Word sense disambiguation is a crucial task in many kinds of natural language I)rot:essing at)l)li- cations, such as word selection in iIla(;hine trans- lation (Sato, 1991), pruning of syntactic struc- tures in parsing (l,ytinen, 1986; Nagao, 11994) an(l text retrieval (Krovets and Croft, 1992; Voorht'.es, 1993). Various researches on word sense disamil)ignation have recently been utilized in (:orlms-based apt)roache.s, reflecting the growth in the numlmr of machine readable texts. Unlike rule-basel1 ~l)l)roa('.hes, eortms-l)asext al)proa(:hes free us fl'om the task of generalizing observed 1)he- nt)Illena to l)roduce rnles for word sense, disaln- ])igmttion, e.g. subt:ittegorization rules. Cortms- based al)proaches are exet:ut(;(1 based on the in- tuitively t'easibh', assmnption that the higher the degree of similarity betwee, n the context of an ill- put word and tim context ill which tit(; word ap- l)cars in a sens(~' in a tort)us , the more plausible it becomes that the word is used in the same s(.~nse. Corpus-/)ased m(;thotls are. classified into two ap- 1)rt)aches: examI)le-I)ased approaches (Kurohashi and Nagao, 1994; Urmnoto, 1994) and statistic- based apl)roa(:hes (l~rown et al., 1991; 1)tLglm and Itai, 1!)94; Niwa and Nitta, 11994; Schiitze, 1992; Ym'owsky, 1995). We follow the examt)h>based apl)roach ill exl)laining its effe.etivity for verb sense disamibiguation in Japanese. A representative example-based method for verb sense disambiguation was proposed by Kuro- hashi and Nagao (Kurohashi's inethod) (Kuro- hashi rand Nagao, 1994). Their method uses an 0,xamph; database, containing examples of colloca- tions as in figure 1. Figure 1 shows a fragment of tim entry associated wittl the Japan(;se verb to'ru. As with most words, the ve, rb to'r"¢t has multi- pie senses, examples of whit:h are "to take/steal," "to attain," "to subst'ril)e" and "to reserve," The database gives one or more case frame(s) associ- ated with tilt', verbs for each of their senses. In .Japanese, a coutI)lelnt;nt Of a verb, which is a con- stituent of the case frame of the verb, consists of a nonii phrase (case filler) followed by a case marker such ms ga (nominative) or o (accusative). The database has ~m example set of case fillers for each case. …

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