A Corpus-based Approach to Automatic Compound Extraction

A Corpus-based Approach to Automatic Compound Extraction Keh-Yih Su Ming-Wen Wu Jing-Shin Chang Dept. of Electrical Engineering Behavior Design Corporation Dept. of Electrical Engineering National Tsing-Hua University No. 28, 2F, R&D Road II National Tsing-Hua University Hsinchu, Taiwan 30043, R.O.C. Science-Based Industrial Park Hsinchu, Talwan 30043, R.O.C. kysu©bdc, com. tw Hsinchu, Taiwan 30077, R.O.C. shin©hera, ee.nthu, edu. 1;w mingwen~bdc, com. tw Abstract An automatic compound retrieval method is pro- posed to extract compounds within a text mes- sage. It uses n-gram mutual information, relative frequency count and parts of speech as the features for compound extraction. The problem is mod- eled as a two-class classification problem based on the distributional characteristics of n-gram to- kens in the compound and the non-compound clus- ters. The recall and precision using the proposed approach are 96.2% and 48.2% for bigram com- pounds and 96.6% and 39.6% for trigram com- pounds for a testing corpus of 49,314 words. A significant cutdown in processing time has been observed. Introduction In technical manuals, technical compounds [Levi 1978] are very common. Therefore, the qual- ity of their translations greatly affects the per- formance of a machine translation system. If a compound is not in the dictionary, it would be translated incorrectly in many cases; the reason is: many compounds are not compositional, which means that the translation of a compound is not the composite of the respective translations of the individual words [Chen and Su 1988]. For exam- ple, the translation of 'green house' into Chinese is not the composite of the Chinese ~anslations of 'green' and 'house'. Under such circumstances, the number of parsing ambiguities will also in- crease due to the large number of possible parts of speech combinations for the individual words. It will then reduce the accuracy rate in disam- biguation and also increase translation time. In practical operations, a computer-translated • manual is usually concurrently processed by sev- eral posteditors; thus, to maintain the consistency of translated terminologies among different poste- ditors is very important, because terminological consistency is a major advaatage of machine trans- lation over human translation. If all the termi- nologies can be entered into the dictionary before translation, the consistency can be automatically maintained, the translation quality can be greatly improved, and lots of postediting time and consis- tency maintenance cost can be saved. Since compounds are rather productive and new compounds are created from day to day, it is impossible to exhaustively store all compounds in a dictionary. Also, it is too costly and time- consuming to inspect the manual by people for the compound candidates and update the dictio- nary beforehand. Therefore, it is important that the compounds be found and entered into the dic- tionary before translation without much human effort; an automatic and quantitative tool for ex- tracting compounds from the text is thus seriously required. Several compound extracting approaches have been proposed in the literature [Bourigault 1992, Calzolari and Bindi 1990]. Traditional rule-based systems are to encode some sets of rules to ex- …

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