KOI at SemEval-2018 Task 5: Building Knowledge Graph of Incidents

Paramita Mirza, Fariz Darari, Rahmad Mahendra

Abstract
We present KOI (Knowledge of Incidents), a system that given news articles as input, builds a knowledge graph (KOI-KG) of incidental events. KOI-KG can then be used to efficiently answer questions such “How many killing incidents happened in 2017 that involve Sean?” The required steps in building the KG include: (i) document preprocessing involving word sense disambiguation, named-entity recognition, temporal expression recognition and normalization, and semantic role labeling; (ii) incidental event extraction and coreference resolution via document clustering; and (iii) KG construction and population.
Anthology ID:
S18-1010
Volume:
Proceedings of the 12th International Workshop on Semantic Evaluation
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
81–87
Language:
URL:
https://aclanthology.org/S18-1010
DOI:
10.18653/v1/S18-1010
Bibkey:
Cite (ACL):
Paramita Mirza, Fariz Darari, and Rahmad Mahendra. 2018. KOI at SemEval-2018 Task 5: Building Knowledge Graph of Incidents. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 81–87, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
KOI at SemEval-2018 Task 5: Building Knowledge Graph of Incidents (Mirza et al., SemEval 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/improve-issue-templates/S18-1010.pdf
PDF Search