Study and Implementation of Combined Techniques for Automatic Extraction of Terminology

Study and Implementation of Combined Techniques for Automatic Extraction of Terminology Bdatrice Daille TALANA University Paris 7 Case 7003 2, Place Jussieu F-75251 Paris Cedex 05 France daille@linguist, j ussieu, fr Abstract This paper presents an original method and its imple- mentation to extract terminology from corpora by com- bining linguistic filters and statistical methods. Start- ing from a linguistic study of the terms of telecommu- nication domain, we designed a number of filters which enable us to obtain a first selection of sequences that may be considered as terms. Various statistical scores are applied to this selection and results are evaluated. This method has been applied to French and to English, but this paper deals only with French. Introduction A terminology bank contains the vocabulary of a tech- nical domain: terms, which refer to its concepts. Building a terminological bank requires a lot of time and both linguistic and technical knowledge. The is- sue, at stake, is the automatic extraction of termi- nology of a specific domain from a corpus. Cur- rent research on extracting terminology uses either lin- guistic specifications or statistical approaches. Con- cerning the former, [Bouriganlt, 1992] has proposed a program which extracts automatically from a cor- pus sequences of lexical units whose morphosyntax characterizes maximal technical noun phrases. This list of sequences is given to a terminologist to be checked. For the latter, several works ([Lafon, 1984], [Church and Hanks, 1990], [Calzolari and Bindi, 1990], [Smadja and McKeown, 1990]) have shown that statis- tical scores are useful to extract collocations from cor- pora. The main problem with one or the other approach is the "noise": indeed, morphosyntactic criteria are not sufficient to isolate terms, and collocations extracted thanks to statistical methods belong to various types of associations: functional, semantical, thematical or un- characterizable ones. Our goal is to use statistical scores for extracting tech- nical compounds only and to forget about the other types of collocations. We proceed in two steps: first, apply a linguistic filter which selects candidates from the corpus; then, apply statistical scores to rank these candidates and select the scores which fit our purpos(~ best, in other words scores that concentrate their high values to terms and their low values to co-occurrcuccs which are not terms. Linguistic Data In a first part, we therefore study the linguistic specifi- cations on the nature of terms in the technical domain of telecommunications for French. Then, taking into ac- count these linguistics results, we present the method and the program which extracts andcounts the candi- date terms. Linguistic specifications Terms are mainly multi-word units of nominal type that could be characterized by a range of morphological, syn- tactic or semantic properties. The main property of nominal terms is the morphosyntactic one: its str,c- ture belongs to well-known morphosyntactic structures such asN ADJ, N1 de N2, etc. that have been studied by [Mathieu-Colas, 1988] for French. Some graphic indica- tions (hyphen), morphological indications (restrictious in flexion) and syntactic ones (absence of determiners) could also be …

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