Abstract
We introduce a method to reduce constituent parsing to sequence labeling. For each word wt, it generates a label that encodes: (1) the number of ancestors in the tree that the words wt and wt+1 have in common, and (2) the nonterminal symbol at the lowest common ancestor. We first prove that the proposed encoding function is injective for any tree without unary branches. In practice, the approach is made extensible to all constituency trees by collapsing unary branches. We then use the PTB and CTB treebanks as testbeds and propose a set of fast baselines. We achieve 90% F-score on the PTB test set, outperforming the Vinyals et al. (2015) sequence-to-sequence parser. In addition, sacrificing some accuracy, our approach achieves the fastest constituent parsing speeds reported to date on PTB by a wide margin.- Anthology ID:
- D18-1162
- Original:
- D18-1162v1
- Version 2:
- D18-1162v2
- Volume:
- Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
- Month:
- October-November
- Year:
- 2018
- Address:
- Brussels, Belgium
- Editors:
- Ellen Riloff, David Chiang, Julia Hockenmaier, Jun’ichi Tsujii
- Venue:
- EMNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1314–1324
- Language:
- URL:
- https://aclanthology.org/D18-1162
- DOI:
- 10.18653/v1/D18-1162
- Cite (ACL):
- Carlos Gómez-Rodríguez and David Vilares. 2018. Constituent Parsing as Sequence Labeling. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 1314–1324, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Constituent Parsing as Sequence Labeling (Gómez-Rodríguez & Vilares, EMNLP 2018)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/D18-1162.pdf
- Code
- aghie/tree2labels