Towards Automatic Extraction of Monolingual and Bilingual Terminology

Toward,q Automatic Extraction of Monolingual and Bilingual q?erminology B(atricc I)AILLI';* - l::,'ic OAUSSIEll - J(.'ali-Mal(; LANCI;; (*)TALANA Univ. Pa,'is 7 k IBM-France, See 3099, 75592 Paris Cedcx 12 Emaih j ml((.0vnet.ibm.conl Abstract In this paper, we make use of linguistic knowledge to identify certain noun phrases, both in English and French, which are likely to be terms. We then test and cmnl)are (lifl'e.r- ent statistical scores to select the "good" ones among tile candidate terms, and finally propose a statistical method to build correspondences of multi-words units across languages. Acknowledgement Most of this work was carried out under project EUII.OTP~A ET-10/63, co-sponsored by the European Economic Conmmnity. 1 Introduction A technical lexicon consists of simple as well as complex lexical units. Complex lexical units are mainly compounds, commonly character- ized by a set of morphosyntactic and semantic criteria (see for example [llenveniste, 1966] for Dench and [tlatcher, 1960] for English). The constitution of a list of technical terms from a specific domain is an important issue in Nat- urM Language Processing, for example in ap- plications such as Machine Translation. Sev- eral methods for the extraction of terms have been proposed, relying on linguistic or statistical approaches. To build a monolingual terminol- ogy bank, [Bourigault, 1{)92] has implemented a software package which provides it list of likely terminologicM units, based on linguistic spec- ifications. Different statistical methods have Mso been tested to extract collocations from large corpora, as [Church and lianks, 1990, Smadja aim McKeown, 1990]. Our work makes use of both linguistic and statistical knowledge. The outline of this paper is the following: lirst, given linguistic specifh:ations of English and l;'rencli terms, we select noun phrases which are likely ta be terms, and which we will call can- didate terms. To build a monolingual termi- nology bank, we then apply different statistical scores to select the good ones among the candi- date terms. Finally, we. test statistical ineth- ods to obtMn ;~ list of bilingual terms, using aligned corpora in l"cench and Ex@ish. All work and tests are carried out on a parallel bilin- gual corpus that is tagged by the words' part- of-speech and lemma. This corpus consists of Mmut 20(I,000 words for each language in the tieht of telecommunications. Simil,~r work can be found in [Van der Eijk, 1993]. 2 Linguistic specifications of French and English terms 2.1 Basic multi-words units From an investigation of the cori)us, and from the tenninologists' point of view (for exam- pie [Nkwenti-Azeh, 1992]), it appears that most of tile terms encountered in technical tiehls are noun phrases corresponding to ~t limited num- I}er of syntactic patterns. These patterns detine the morphosyntactic structures of multi-words units (MWU) which are likely to be terms. We detine the length of a MWU as the number of main items it contains. A main item is either a noun, an adjective, a verb or an adverb; thus, neither deternliners nor prepositions are consid- ered main items. MWU of length 1 often corre- spond to words connected …

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