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Temporally anchored spatial knowledge: Corpora and experiments

Published online by Cambridge University Press:  20 May 2020

Alakananda Vempala  and
Eduardo Blanco
Alakananda Vempala*
Affiliation:
Department of Computer Science and Engineering, University of North Texas, Denton, TX76207, USA
Eduardo Blanco
Affiliation:
Department of Computer Science and Engineering, University of North Texas, Denton, TX76207, USA
*
*Corresponding author. E-mail: AlakanandaVempala@my.unt.edu
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Abstract

This article presents a two-step methodology to annotate temporally anchored spatial knowledge on top of OntoNotes. We first generate potential knowledge using semantic roles or syntactic dependencies and then crowdsource annotations to validate the potential knowledge. The resulting annotations indicate how long entities are or are not located somewhere and temporally anchor this spatial information. We present an in-depth corpus analysis comparing the spatial knowledge generated by manipulating roles or dependencies. Experiments show that working with syntactic dependencies instead of semantic roles allows us to generate more potential entity-related spatial knowledge and obtain better results in a realistic scenario, that is, with predicted linguistic information.

Keywords

Spatial knowledgeInformation extraction
Type
Article
Information
Natural Language Engineering , Volume 27 , Issue 5 , September 2021 , pp. 519 - 543
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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