Abstract
We introduce a constituency parser based on a bi-LSTM encoder adapted from recent work (Cross and Huang, 2016b; Kiperwasser and Goldberg, 2016), which can incorporate a lower level character biLSTM (Ballesteros et al., 2015; Plank et al., 2016). We model two important interfaces of constituency parsing with auxiliary tasks supervised at the word level: (i) part-of-speech (POS) and morphological tagging, (ii) functional label prediction. On the SPMRL dataset, our parser obtains above state-of-the-art results on constituency parsing without requiring either predicted POS or morphological tags, and outputs labelled dependency trees.- Anthology ID:
- E17-2053
- Volume:
- Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Mirella Lapata, Phil Blunsom, Alexander Koller
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 331–336
- Language:
- URL:
- https://aclanthology.org/E17-2053
- DOI:
- Cite (ACL):
- Maximin Coavoux and Benoît Crabbé. 2017. Multilingual Lexicalized Constituency Parsing with Word-Level Auxiliary Tasks. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 331–336, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Multilingual Lexicalized Constituency Parsing with Word-Level Auxiliary Tasks (Coavoux & Crabbé, EACL 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/E17-2053.pdf
- Code
- mcoavoux/mtg