A Cluster Ranking Model for Full Anaphora Resolution

Juntao Yu, Alexandra Uma, Massimo Poesio


Abstract
Anaphora resolution (coreference) systems designed for the CONLL 2012 dataset typically cannot handle key aspects of the full anaphora resolution task such as the identification of singletons and of certain types of non-referring expressions (e.g., expletives), as these aspects are not annotated in that corpus. However, the recently released dataset for the CRAC 2018 Shared Task can now be used for that purpose. In this paper, we introduce an architecture to simultaneously identify non-referring expressions (including expletives, predicative s, and other types) and build coreference chains, including singletons. Our cluster-ranking system uses an attention mechanism to determine the relative importance of the mentions in the same cluster. Additional classifiers are used to identify singletons and non-referring markables. Our contributions are as follows. First all, we report the first result on the CRAC data using system mentions; our result is 5.8% better than the shared task baseline system, which used gold mentions. Second, we demonstrate that the availability of singleton clusters and non-referring expressions can lead to substantially improved performance on non-singleton clusters as well. Third, we show that despite our model not being designed specifically for the CONLL data, it achieves a score equivalent to that of the state-of-the-art system by Kantor and Globerson (2019) on that dataset.
Anthology ID:
2020.lrec-1.2
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
11–20
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.2
DOI:
Bibkey:
Cite (ACL):
Juntao Yu, Alexandra Uma, and Massimo Poesio. 2020. A Cluster Ranking Model for Full Anaphora Resolution. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 11–20, Marseille, France. European Language Resources Association.
Cite (Informal):
A Cluster Ranking Model for Full Anaphora Resolution (Yu et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.2.pdf
Code
 juntaoy/dali-full-anaphora
Data
CoNLLCoNLL-2012