Dependency Parsing of Code-Switching Data with Cross-Lingual Feature Representations

نویسنده

  • Niko Partanen
چکیده

This paper describes the test of a dependency parsing method which is based on bidirectional LSTM feature representations and multilingual word embedding, and evaluates the results on monoand multilingual data. The results are similar in all cases, with a slightly better results achieved using multilingual data. The languages under investigation are Komi-Zyrian and Russian. Examination of the results by relation type shows that some language specific constructions are correctly recognized even when they appear in naturally occurring code-switching data.

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تاریخ انتشار 2017