Multilingual Back-and-Forth Conversion between Content and Function Head for Easy Dependency Parsing

Ryosuke Kohita, Hiroshi Noji, Yuji Matsumoto


Abstract
Universal Dependencies (UD) is becoming a standard annotation scheme cross-linguistically, but it is argued that this scheme centering on content words is harder to parse than the conventional one centering on function words. To improve the parsability of UD, we propose a back-and-forth conversion algorithm, in which we preprocess the training treebank to increase parsability, and reconvert the parser outputs to follow the UD scheme as a postprocess. We show that this technique consistently improves LAS across languages even with a state-of-the-art parser, in particular on core dependency arcs such as nominal modifier. We also provide an in-depth analysis to understand why our method increases parsability.
Anthology ID:
E17-2001
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
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–7
Language:
URL:
https://aclanthology.org/E17-2001
DOI:
Bibkey:
Cite (ACL):
Ryosuke Kohita, Hiroshi Noji, and Yuji Matsumoto. 2017. Multilingual Back-and-Forth Conversion between Content and Function Head for Easy Dependency Parsing. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 1–7, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
Multilingual Back-and-Forth Conversion between Content and Function Head for Easy Dependency Parsing (Kohita et al., EACL 2017)
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PDF:
https://preview.aclanthology.org/update-css-js/E17-2001.pdf
Code
 kohilin/MultiBFConv