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

Paramita Mirza, Fariz Darari, Rahmad Mahendra

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

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 as “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.

Original languageEnglish
Title of host publicationNAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop
EditorsMarianna Apidianaki, Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
PublisherAssociation for Computational Linguistics (ACL)
Pages81-87
Number of pages7
ISBN (Electronic)9781948087209
Publication statusPublished - 2018
Event12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the - New Orleans, United States
Duration: 5 Jun 20186 Jun 2018

Publication series

NameNAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop

Conference

Conference12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the
Country/TerritoryUnited States
CityNew Orleans
Period5/06/186/06/18

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