Cross-Lingual Dependency Parsing Using Code-Mixed TreeBank

September 05, 2019 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Zhang Meishan, Zhang Yue, Fu Guohong arXiv ID 1909.02235 Category cs.CL: Computation & Language Citations 40 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 4 months ago
Abstract
Treebank translation is a promising method for cross-lingual transfer of syntactic dependency knowledge. The basic idea is to map dependency arcs from a source treebank to its target translation according to word alignments. This method, however, can suffer from imperfect alignment between source and target words. To address this problem, we investigate syntactic transfer by code mixing, translating only confident words in a source treebank. Cross-lingual word embeddings are leveraged for transferring syntactic knowledge to the target from the resulting code-mixed treebank. Experiments on University Dependency Treebanks show that code-mixed treebanks are more effective than translated treebanks, giving highly competitive performances among cross-lingual parsing methods.
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