arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1908.10461cs.CL

A survey of cross-lingual features for zero-shot cross-lingual semantic parsing

Georgia Institute of Technology(佐治亚理工学院);Samsung AI Center(三星人工智能中心);University of Edinburgh(爱丁堡大学)

Jingfeng Yang, Federico Fancellu, Bonnie Webber

英文摘要:

The availability of corpora to train semantic parsers in English has lead to significant advances in the field. Unfortunately, for languages other than English, annotation is scarce and so are developed parsers. We then ask: could a parser trained in English be applied to language that it hasn't been trained on? To answer this question we explore zero-shot cross-lingual semantic parsing where we train an available coarse-to-fine semantic parser (Liu et al., 2018) using cross-lingual word embeddings and universal dependencies in English and test it on Italian, German and Dutch. Results on the Parallel Meaning Bank - a multilingual semantic graphbank, show that Universal Dependency features significantly boost performance when used in conjunction with other lexical features but modelling the UD structure directly when encoding the input does not.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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