Temporally anchored spatial knowledge: Corpora and experiments

Alakananda Vempala, Eduardo Blanco

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)519-543
Number of pages25
JournalNatural Language Engineering
Issue number5
StatePublished - Sep 2021
Externally publishedYes


  • Information extraction
  • Spatial knowledge

ASJC Scopus subject areas

  • Software
  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence


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