Multilingual Lexicalized Constituency Parsing with Word-Level Auxiliary Tasks

TitreMultilingual Lexicalized Constituency Parsing with Word-Level Auxiliary Tasks
Publication TypeArticle dans des actes
Année de la conférence2017
AuthorsCoavoux, Maximin, and Benoît Crabbé
Nom de la conférenceProceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
Date de publicationApril
PublisherAssociation for Computational Linguistics
Conference LocationValencia, Spain

We introduce a constituency parser based on a bi-LSTM encoder adapted from re- cent work (Cross and Huang, 2016b; Kiperwasser and Goldberg, 2016), which can incorporate a lower level character bi- LSTM (Ballesteros et al., 2015; Plank et al., 2016). We model two important in- terfaces of constituency parsing with aux- iliary tasks supervised at the word level: (i) part-of-speech (POS) and morpholog- ical tagging, (ii) functional label predic- tion. On the SPMRL dataset, our parser obtains above state-of-the-art results on constituency parsing without requiring ei- ther predicted POS or morphological tags, and outputs labelled dependency trees.