Encoding a Parallel Corpus for Automatic Terminology Extraction

Proceedings of EACL '99 Encoding a Parallel Corpus for Automatic Terminology Extraction Johann Gamper European Academy Bolzano/Bozen Weggensteinstr. 12/A, 39100 Bolzano/Bozen, Italy j gamper@eurac, edu Abstract We present a status report about an ongoing research project in the field of (semi-)automatic terminology acquisi- tion at the European Academy Bolzano. The main focus will be on encoding a text corpus, which serves as a basis for applying term extraction programq. 1 Introduction Text corpora are valuable resources in all areas dealing with natural language processing in one form or another. Terminology is one of these fields, where researchers explore domain-specific language material to investigate terminological is- sues. The manual acquisition of terminological data from text material is a very work-intensive and error-prone task. Recent advances in auto- matic corpus analysis favored a modern form of terminology acquisition: (1) a corpus is a col- lection of language material in machine-readable form and (2) computer programs scan the cor- pus for terminologically relevant information and generate lists of term candidates which have to be post-edited by humans. The following project CATEx adopts this approach. 2 The CATEx Project Due to the equal status of the Italian and the Ger- man language in South Tyrol, legal and admin- istrative documents have to be written in both languages. A prerequisite for high quality trans- lations is a consistent and comprehensive bilingual terminology, which also forms the basis for an in- dependent German legal language which reflects the Italian legislation. The first systematic effort in this direction was initiated a few years ago at the European Academy Bolzano/Bozen with the goal to compile an Italian/German legal and ad- ministrative terminology for South Tyrol. The CATEx (C_omputer A_.ssisted Terminology E___~raction) project emerged from the need to sup- port and improve, both qualitatively and quan- titatively, the manual acquisition of terminologi- cal data. Thus, the main objective of CATEx is the development of a computational framework for (semi-)antomatic terminology acquisition, which consists of four modules: a parallel text corpus, term-extraction programs, a term bank linked to the text corpus, and a user-interface for browsing the corpus and the term bank. 3 Building a Parallel Text Corpus Building the text corpus comprises the following tasks: corpus design, preprocessing, encoding pri- mary data, and encoding linguistic information. 3.1 Corpus Design and Preprocessing Corpus design selects a collection of texts which should be included in the corpus. An important criteria is that the texts represent a realistic model of the language to be studied (Bowker, 1996). In its current form, our corpus contains only one sort of texts, namely the bilingual version of Italian laws such as the Civil Code. A particular feature of our corpus, which contains both German and Italian translations, is the structural equivalence of the original text and its translation down to the sentence level, i.e. each sentence in the original text has a corresponding one in the translation. The corpus is one of the largest special language corpora. It contains ca. 5 Mio. words and 35,898 …

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