Resolving translation ambiguity using monolingual corpora

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Abstract

In the bilingual track of CLEF 2002, focusing on word translation ambiguity, we experimented with several techniques for choosing the best target translation for each source query word by using co-occurrence statistics in a reference corpus consisting of documents in the target language. Our techniques give one best translation per source query word. We also experimented with combining these word choice results in the final translated query. The source query languages were Spanish, Chinese, and Japanese; the target language documents were in English. For Spanish-to-English retrieval, the best recall and average precision of Spanish-to-English retrieval reached 95% and 97%, respectively, of the recall and average precision of an English monolingual retrieval run. For Chinese-to-English text retrieval, the recall and average precision reached 89% and 60%, respectively, of the English run. For Japanese-to-English text retrieval, the best recall and average precision reached 82% and 69%, respectively, of the English run. © Springer-Verlag Berlin Heidelberg 2003.

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APA

Qu, Y., Grefenstette, G., & Evans, D. A. (2003). Resolving translation ambiguity using monolingual corpora. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2785, 223–241. https://doi.org/10.1007/978-3-540-45237-9_19

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