@inproceedings{spaulding-etal-2023-darpa,
title = "The {DARPA} {W}ikidata Overlay: {W}ikidata as an ontology for natural language processing",
author = "Spaulding, Elizabeth and
Conger, Kathryn and
Gershman, Anatole and
Uceda-Sosa, Rosario and
Brown, Susan Windisch and
Pustejovsky, James and
Anick, Peter and
Palmer, Martha",
editor = "Bunt, Harry",
booktitle = "Proceedings of the 19th Joint ACL-ISO Workshop on Interoperable Semantics (ISA-19)",
month = jun,
year = "2023",
address = "Nancy, France",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.isa-1.1",
pages = "1--10",
abstract = "With 102,530,067 items currently in its crowd-sourced knowledge base, Wikidata provides NLP practitioners a unique and powerful resource for inference and reasoning over real-world entities. However, because Wikidata is very entity focused, \textit{events} and \textit{actions} are often labeled with eventive nouns (e.g., the process of diagnosing a person{'}s illness is labeled {``}diagnosis{''}), and the typical participants in an event are not described or linked to that event concept (e.g., the medical professional or patient). Motivated by a need for an adaptable, comprehensive, domain-flexible ontology for information extraction, including identifying the roles entities are playing in an event, we present a curated subset of Wikidata in which events have been enriched with PropBank roles. To enable richer narrative understanding between events from Wikidata concepts, we have also provided a comprehensive mapping from temporal Qnodes and Pnodes to the Allen Interval Temporal Logic relations.",
}
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<abstract>With 102,530,067 items currently in its crowd-sourced knowledge base, Wikidata provides NLP practitioners a unique and powerful resource for inference and reasoning over real-world entities. However, because Wikidata is very entity focused, events and actions are often labeled with eventive nouns (e.g., the process of diagnosing a person’s illness is labeled “diagnosis”), and the typical participants in an event are not described or linked to that event concept (e.g., the medical professional or patient). Motivated by a need for an adaptable, comprehensive, domain-flexible ontology for information extraction, including identifying the roles entities are playing in an event, we present a curated subset of Wikidata in which events have been enriched with PropBank roles. To enable richer narrative understanding between events from Wikidata concepts, we have also provided a comprehensive mapping from temporal Qnodes and Pnodes to the Allen Interval Temporal Logic relations.</abstract>
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%0 Conference Proceedings
%T The DARPA Wikidata Overlay: Wikidata as an ontology for natural language processing
%A Spaulding, Elizabeth
%A Conger, Kathryn
%A Gershman, Anatole
%A Uceda-Sosa, Rosario
%A Brown, Susan Windisch
%A Pustejovsky, James
%A Anick, Peter
%A Palmer, Martha
%Y Bunt, Harry
%S Proceedings of the 19th Joint ACL-ISO Workshop on Interoperable Semantics (ISA-19)
%D 2023
%8 June
%I Association for Computational Linguistics
%C Nancy, France
%F spaulding-etal-2023-darpa
%X With 102,530,067 items currently in its crowd-sourced knowledge base, Wikidata provides NLP practitioners a unique and powerful resource for inference and reasoning over real-world entities. However, because Wikidata is very entity focused, events and actions are often labeled with eventive nouns (e.g., the process of diagnosing a person’s illness is labeled “diagnosis”), and the typical participants in an event are not described or linked to that event concept (e.g., the medical professional or patient). Motivated by a need for an adaptable, comprehensive, domain-flexible ontology for information extraction, including identifying the roles entities are playing in an event, we present a curated subset of Wikidata in which events have been enriched with PropBank roles. To enable richer narrative understanding between events from Wikidata concepts, we have also provided a comprehensive mapping from temporal Qnodes and Pnodes to the Allen Interval Temporal Logic relations.
%U https://aclanthology.org/2023.isa-1.1
%P 1-10
Markdown (Informal)
[The DARPA Wikidata Overlay: Wikidata as an ontology for natural language processing](https://aclanthology.org/2023.isa-1.1) (Spaulding et al., ISA-WS 2023)
ACL
- Elizabeth Spaulding, Kathryn Conger, Anatole Gershman, Rosario Uceda-Sosa, Susan Windisch Brown, James Pustejovsky, Peter Anick, and Martha Palmer. 2023. The DARPA Wikidata Overlay: Wikidata as an ontology for natural language processing. In Proceedings of the 19th Joint ACL-ISO Workshop on Interoperable Semantics (ISA-19), pages 1–10, Nancy, France. Association for Computational Linguistics.