Semi-Automatic Acquisition of Domain-Specific Translation Lexicons

Semi-Automatic Acquisition of Domain-Specific Translation Lexicons Philip Resnik Dept. of Linguistics and UMIACS University of Maryland College Park, MD 20742 USA resnik~umiacs, umd. edu I. Dan Melamed Dept. of Computer and Information Science University of Pennsylvania Philadelphia, PA 19104 USA melamed©unagi, cis. upenn, edu Abstract We investigate the utility of an algo- rithm for translation lexicon acquisition (SABLE), used previously on a very large corpus to acquire general translation lexi- cons, when that algorithm is applied to a much smaller corpus to produce candidates for domain-specific translation lexicons. 1 Introduction Reliable translation lexicons are useful in many ap- plications, such as cross-language text retrieval. Al- though general purpose machine readable bilingual dictionaries are sometimes available, and although some methods for acquiring translation lexicons au- tomatically from large corpora have been proposed, less attention has been paid to the problem of ac- quiring bilingual terminology specific to a domain, especially given domain-specific parallel corpora of only limited size. In this paper, we investigate the utility of an algo- rithm for translation lexicon acquisition (Melamed, 1997), used previously on a very large corpus to ac- quire general translation lexicons, when that algo- rithm is applied to a much smaller corpus to produce candidates for domain-specific translation lexicons. The goal is to produce material suitable for post- processing in a lexicon acquisition process like the following: 1. Run the automatic lexicon acquisition algo- rithm on a domain-specific parallel corpus. 2. Automatically filter out "general usage" entries that already appear in a machine readable dic- tionary (MRD) or other general usage lexical resources. 3. Manually filter out incorrect or irrelevant en- tries from the remaining list. Our aim, therefore, is to achieve sufficient recall and precision to make this process -- in particular the time and manual effort required in Step 3 -- a viable alternative to manual creation of translation lexicons without automated assistance. The literature on cross-lingual text retrieval (CLTR) includes work that is closely related to this research, in that recent approaches emphasize the use of dictionary- and corpus-based techniques for translating queries from a source language into the language of the document collection (Oard, 1997). Davis and Dunning (1995), for example, generate target-language queries using a corpus-based tech- nique that is similar in several respects to the work described here. However, the approach does not at- tempt to distinguish domain-specific from general usage term pairs, and it involves no manual inter- vention. The work reported here, focusing on semi- automating the process of acquiring translation lexi- cons specific to a domain, can be viewed as providing bilingual dictionary entries for CLTR methods like that used by Davis in later work (Davis, 1996), in which dictionary-based generation of an ambiguous target language query is followed by corpus-based disambiguation of that query. Turning to the literature on bilingual terminology identification per se, although monolingual termi- nology extraction is a problem that has been previ- ously explored, often with respect to identifying rel- evant multi-word terms (e.g. (Daille, 1996; Smadja, 1993)), less prior …

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