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
- Venues:
- SemEval | *SEM
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 81–87
- Language:
- URL:
- https://aclanthology.org/S18-1010
- DOI:
- 10.18653/v1/S18-1010
- 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-*SEM 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S18-1010.pdf