Temporally anchored spatial knowledge: Corpora and experiments. (20th September 2021)

• Record Type: Journal Article
• Authors: Vempala, Alakananda; Blanco, Eduardo
• Is Part Of: Natural language engineering. Volume 27:Part 5(2021)
• Page Start: 519
• Page End: 543
• Publication Date: 2021-09-20
• Subjects: Spatial knowledge -- Information extraction; Natural language processing (Computer science) -- Periodicals; Software engineering -- Periodicals; 006.35
• DOI: 10.1017/S1351324920000212
• Languages: English
• ISSNs: 1351-3249

Abstract

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.