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Temporally anchored spatial knowledge: Corpora and experiments

  • Natural Language Engineering
  • Cambridge University Press
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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.

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DOI
10.1017/s1351324920000212
OpenAlex
W3028183297
Document type
article
Language
EN
Source
Natural Language Engineering
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