Word Knowledge Acquisition, Lexicon Construction and Dictionary Compilation

Word Knowledge Acquisition, Lexicon Construction and Dictionary Compilation Antonio Sanfilippo* SIIARP l,M)oratorics of l';urol)c l,td. Oxford Science Park, Oxford ()X4 4(]A, UK ant onio~sharp, co. uk Abstract We describe an approach to semiautomatic lex- icon development from |nachine readal)le dictio- naries with specific reference to verbal diatlleses, envisaging ways in which tile results obtained can be used to guide word classification in the con- strnction of dictionary datal)ases. 1 Introduction The acquisition and representation of lexical knowl- edge from machine-readable dictionaries and text cor- pora have increasingly become major concerns in Com- putational Lexicography/Lexicology. While this trend was essentially set by the need to mmximize cost- effectiveness in building large scale Lexical Knowledge Bases for NLP (LKBs), there is a clear sense in which the construction of such knowledge I)ascs also caters to the demand for better dictionaries. Currently available dictionaries and thesauri provide an undoubtedly rich source of lexical information, but often omit or neglect to make explicit salient syntactic and semantic proper- ties of word entries. For exa|nplc, it is well known that the same verb sense can appear in a wtriety of snl)cat- egorization frames which can be related to one at|other through valency alternations (diatheses). Some dictio- naries provide subcategorization information by means of grammar codes, as shown below for the "sail" sense. of the verb dock in LI)OCE -- Longman's Dictionary of Contemporary English (Procter, 1978). (1) a,,,:k "| , [Tl;m: ("0] .... The codes [T1;10:(at)] indicate that the vcrl) can bc either transitive or intransitive with the possible a(I- dition of all oblique colnpienlent introduced by l.he preposition at: (2) a. [T1 (at)]: Kim docked his ship (at Clasgow) b. [IO (at)l: The ship docked (at Glasgow) Unfortunately, an indication of diatheses which relate the various occurrences of tt,e verb to one another is rarely provided. Consequently, if we were to use the grammar code information found in M)OCE to cre- ate verb entries in an I,I(B by automatic conversion we would construct four seemingly vnrelated entries for the verb dock (see §3). Inadequacies of this kind may be redressed through semiantomatie techniques *The researcl, relmrted in this paper was carried out within the ACQUILFX project. Iatn indebted to Ted Briscoe, Ann Col)estake and Pete Whitek)ck for helpful comments. wl|ich make it possil)le to suplfly infornmtion concern- ing amenability to diathesis alternations so ~tq to avoid expanding distinct entries for related uses of the same verb. This practice woldd allow us to develop an I,KB from dictionary databases which offers a more co|n- plate and linguistically relined repository of lexical in- formation l, hall the source databases. Such an ],Kll wouhl be used to generate lexical components for NI,P systems, and couhl also be integrated into a lexicogra- pher's workstation to guide word classification. 2 The ACQUILEX Lexicon Development Environnmnt Our points of departure are tile tools for lexical acqui- sition and knowledge representation (lew~loped iL~ part of the ACQUII,I'3X project ('The Acquisition of Lcxieal Knowledge for NLP Systems'). The ACQUILI'~X l,exicon l)evelopment Environ- …

Content truncated to 500 words