@inproceedings{mirza-etal-2018-koi,
title = "{KOI} at {S}em{E}val-2018 Task 5: Building Knowledge Graph of Incidents",
author = "Mirza, Paramita and
Darari, Fariz and
Mahendra, Rahmad",
editor = "Apidianaki, Marianna and
Mohammad, Saif M. and
May, Jonathan and
Shutova, Ekaterina and
Bethard, Steven and
Carpuat, Marine",
booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S18-1010",
doi = "10.18653/v1/S18-1010",
pages = "81--87",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T KOI at SemEval-2018 Task 5: Building Knowledge Graph of Incidents
%A Mirza, Paramita
%A Darari, Fariz
%A Mahendra, Rahmad
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Bethard, Steven
%Y Carpuat, Marine
%S Proceedings of the 12th International Workshop on Semantic Evaluation
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F mirza-etal-2018-koi
%X 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.
%R 10.18653/v1/S18-1010
%U https://aclanthology.org/S18-1010
%U https://doi.org/10.18653/v1/S18-1010
%P 81-87
Markdown (Informal)
[KOI at SemEval-2018 Task 5: Building Knowledge Graph of Incidents](https://aclanthology.org/S18-1010) (Mirza et al., SemEval 2018)
ACL