The Development of Lexical Resources for Information Extraction from Text Combining WordNet and Dewey Decimal Classification

Proceedings of EACL '99 The Development of Lexical Resources for Information Extraction from Text Combining WordNet and Dewey Decimal Classification* Gabriela Cavagli~t ITC-irst Centro per la Ricerca Scientifica e Tecnologica via Sommarive, 18 38050 Povo (TN), ITALY e-mail: cavaglia@irst.itc.it Abstract Lexicon definition is one of the main bot- tlenecks in the development of new ap- plications in the field of Information Ex- traction from text. Generic resources (e.g., lexical databases) are promising for reducing the cost of specific lexica defi- nition, but they introduce lexical ambi- guity. This paper proposes a methodol- ogy for building application-specific lex- ica by using WordNet. Lexical ambiguity is kept under control by marking synsets in WordNet with field labels taken from the Dewey Decimal Classification. 1 Introduction One of the current issues in Information Extrac- tion (IE) is efficient transportability, as the cost of new applications is one of the factors limiting the market. The lexicon definition process is cur- rently one of the main bottlenecks in producing applications. As a matter of fact the necessary lex- icon for an average application is generally large (hundreds to thousands of words) and most lexical information is not transportable across domains. The problem of lexicon transport is worsened by the growing degree of lexicalization of IE systems: nowadays several successful systems adopt lexical rules at many levels. The IE research mainstream focused essentially on the definition of lexica starting from a corpus sample (Riloff, 1993; Grishman, 1997) with the implicit assumption that a corpus provided for an application is representative of the whole applica- *This work was carried on at ITC-IRST as part of the author's dissertation for the degree in Philosophy (University of Turin, supervisor: Carla Bazzanella). The author wants to thank her supervisor at ITC- IRST, Fabio Ciravegna, for his constant help. Alberto Lavelli provided valuable comments to the paper. tion requirement. Unfortunately one of the cur- rent trends in IE is the progressive reduction of the size of training corpora: e.g., from the 1,000 texts of the MUC-5 (MUC-5, 1993) to the 100 texts in MUC-6 (MUC-6, 1995). When the cor- pus size is limited, the assumption of lexical rep- resentativeness of the sample corpus may not hold any longer, and the problem of producing a repre- sentative lexicon starting from the corpus lexicon arises (Grishman, 1995). Generic resources are interesting as they con- tain (among others) most of the terms necessary for an IE application. Nevertheless up to now the use of generic resources within IE system has been limited for two main reasons. First the in- formation associated to each term is often not de- tailed enough for describing the relations neces- sary for a IE lexicon; secondly the presence of a large amount of lexical polysemy. In this paper we propose a methodology for semi-automatically developing the relevant part of a lexicon (foreground lexicon) for IE applications by using both a small corpus and WordNet. 2 Developing IE Lexical Resources Lexical information in IE can be divided into three sources …

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