Dependency Parsing of Code-Switching Data with Cross-Lingual Feature Representations
Niko Partanen, KyungTae Lim, Michael Rießler, Thierry Poibeau · 2018
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 mono-and 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. TiivistelmäTutkimus arvioi dependenssianalyysin menetelmää, joka perustuu kaksisuuntaiseen LSTM-piirrerepresentaatioon ja monikieliseen 'word embedding' -malliin, sekä arvioi tuloksia yksi-ja monikielisissä aineistoissa.Tulokset ovat