Constituent Parsing as Sequence Labeling
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Constituent Parsing as Sequence LabelingDate
2018Citation
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.
Abstract
[Absctract]: 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.
Keywords
Constituent Parsing
Penn Treebank
Sequence Labeling
Nonterminal Symbols
Penn Treebank
Sequence Labeling
Nonterminal Symbols
Description
EMNLP 2018, Square Meeting Center, Brussels. From October 31st through November 4th.
Editor version
Rights
Atribución 3.0 España
ISBN
978-1-948087-84-1