Graph Based Decoding for Event Sequencing and Coreference Resolution

Zhengzhong Liu, Teruko Mitamura, Eduard Hovy


Abstract
Events in text documents are interrelated in complex ways. In this paper, we study two types of relation: Event Coreference and Event Sequencing. We show that the popular tree-like decoding structure for automated Event Coreference is not suitable for Event Sequencing. To this end, we propose a graph-based decoding algorithm that is applicable to both tasks. The new decoding algorithm supports flexible feature sets for both tasks. Empirically, our event coreference system has achieved state-of-the-art performance on the TAC-KBP 2015 event coreference task and our event sequencing system beats a strong temporal-based, oracle-informed baseline. We discuss the challenges of studying these event relations.
Anthology ID:
C18-1309
Volume:
Proceedings of the 27th International Conference on Computational Linguistics
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico, USA
Editors:
Emily M. Bender, Leon Derczynski, Pierre Isabelle
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3645–3657
Language:
URL:
https://aclanthology.org/C18-1309
DOI:
Bibkey:
Cite (ACL):
Zhengzhong Liu, Teruko Mitamura, and Eduard Hovy. 2018. Graph Based Decoding for Event Sequencing and Coreference Resolution. In Proceedings of the 27th International Conference on Computational Linguistics, pages 3645–3657, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
Cite (Informal):
Graph Based Decoding for Event Sequencing and Coreference Resolution (Liu et al., COLING 2018)
Copy Citation:
PDF:
https://aclanthology.org/C18-1309.pdf