Towards an Automatic Classification of Illustrative Examples in a Large Japanese-French Dictionary Obtained by OCR

Abstract : This paper focuses on improving the Cesselin, a large, open source Japanese-French bilingual dictionary digitalized by OCR, available on the web, and contributively improvable online. Labelling its examples (about 226,000) would significantly enhance their usefulness for language learners. Examples are proverbs, idiomatic constructions, normal usage examples, and, for nouns, phrases containing a quantifier. Proverbs are easy to spot, but not the other types. To find a method for automatically or at least semi-automatically annotating them, we have studied many entries, and hypothesized that the degree of lexical similarity between results of MT into a third language might give good cues. To confirm that hypothesis, we sampled 500 examples and used Google Translate to translate into English the Cesslin Japanese expressions and their French translations. The hypothesis holds well, in particular for distinguishing examples of normal usage from idiomatic examples. Finally, we propose a detailed annotation procedure and discuss its future automatization.
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Mutsuko Tomokiyo, Christian Boitet, Mathieu Mangeot. Towards an Automatic Classification of Illustrative Examples in a Large Japanese-French Dictionary Obtained by OCR. First Workshop on Linguistic Resources for Natural Language Processing, Aug 2018, Santa Fe, United States. pp.112 - 121. ⟨hal-01998453⟩

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