Projection-based Coreference Resolution Using Deep Syntax

Michal Novák, Anna Nedoluzhko, Zdeněk Žabokrtský


Abstract
The paper describes the system for coreference resolution in German and Russian, trained exclusively on coreference relations project ed through a parallel corpus from English. The resolver operates on the level of deep syntax and makes use of multiple specialized models. It achieves 32 and 22 points in terms of CoNLL score for Russian and German, respectively. Analysis of the evaluation results show that the resolver for Russian is able to preserve 66% of the English resolver’s quality in terms of CoNLL score. The system was submitted to the Closed track of the CORBON 2017 Shared task.
Anthology ID:
W17-1508
Volume:
Proceedings of the 2nd Workshop on Coreference Resolution Beyond OntoNotes (CORBON 2017)
Month:
April
Year:
2017
Address:
Valencia, Spain
Editors:
Maciej Ogrodniczuk, Vincent Ng
Venue:
CORBON
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
56–64
Language:
URL:
https://aclanthology.org/W17-1508
DOI:
10.18653/v1/W17-1508
Bibkey:
Cite (ACL):
Michal Novák, Anna Nedoluzhko, and Zdeněk Žabokrtský. 2017. Projection-based Coreference Resolution Using Deep Syntax. In Proceedings of the 2nd Workshop on Coreference Resolution Beyond OntoNotes (CORBON 2017), pages 56–64, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
Projection-based Coreference Resolution Using Deep Syntax (Novák et al., CORBON 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-1508.pdf
Data
OntoNotes 5.0