Detecting Novel Compounds: The Role of Distributional Evidence

Detecting Novel Compounds: The Role of Distributional Evidence Mirella Lapata Department of Computer Science University of Sheffield Regent Court, 211 Portobello Street Sheffield 51 4DP, UK mlap@dcs.shef.ac.uk Alex Lascarides School of Informatics The University of Edinburgh 2 Buccleuch Place Edinburgh EH8 9LW, UK alex@inf.ed.ac.uk Abstract Research on the discovery of terms from corpora has focused on word sequences whose recurrent occurrence in a corpus is indicative of their terminological sta- tus, and has not addressed the issue of discovering terms when data is sparse. This becomes apparent in the case of noun compounding, which is extremely productive: more than half of the candi- date compounds extracted from a corpus are attested only once. We show how ev- idence about established (i.e., frequent) compounds can be used to estimate fea- tures that can discriminate rare valid compounds from rare nonce terms in ad- dition to a variety of linguistic features than can be easily gleaned from corpora without relying on parsed text. 1 Introduction The nature and properties of compounds have been studied at length in the theoretical linguistics literature. It is a well-known fact that compound noun formation in English is relatively produc- tive (see (1)). Although compounds are typically binary (see (1a,b)), they can be also longer than two words (see (le)). Compounds are commonly written as a concatenation of words (see (1a,b)), or as single words (see (lc)), sometimes a hyphen is also used (see (le)). income tax AT & T headquarters bathroom public-relations income-tax relief The use of noun compounds is frequent not only in technical writing and newswire text (McDonald, 1982) but also in fictional prose (Leonard, 1984), and spoken language (Liberman and Sproat, 1992). Novel compounds are used as a text compression device (Marsh, 1984), i.e., to pack meaning into a minimal amount of linguistic structure, as a deictic device, or as a means to clas- sify an entity which has no specific name (Down- ing, 1977). Computational investigations of compound nouns have concentrated on their automatic ac- quisition from corpora, syntactic disambiguation (i.e., determine the structure of compounds like income tax relief), and semantic interpretation (i.e., determine the semantic relation between in- come and tax in income tax). The acquisition of compound nouns is usually subsumed under the general discovery of terms from corpora. Terms are typically acquired by either symbolic or sta- tistical means. Under a symbolic approach, can- didate terms are extracted from the corpus us- ing surface syntactic analysis (Lauer, 1995; Juste- son and Katz, 1995; Bourigault and Jacquemin, 1999) and sometimes are further submitted to ex- perts for manual inspection. The approach typi- cally assumes no prior terminological knowledge, although Jacquemin (1996) proposed the detection of terminological variants in a corpus by making use of lists of existing terms. The main assumption underlying the statistical approach to term acquisition is that lexically as- sociated words tend to appear together more of- ten than expected on the basis of their individual occurrence frequencies. Once candidate terms are detected in the corpus, …

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