Fuzzy-Based Language Grounding of Geographical References: From Writers to Readers

Alejandro Ramos, Jose M. Alonso* (Corresponding Author), Ehud Reiter, Kees Van Deemter, Albert Gatt

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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We describe an applied methodology to build fuzzy models of geographical expressions, which are meant to be used for natural language generation purposes. Our approach encompasses a language grounding task within the development of an actual data-to-text system for the generation of textual descriptions of live weather data. For this, we gathered data from meteorologists through a survey and built consistent fuzzy models that aggregate the interpersonal variations found among the experts. A subset of the models was utilized in an illustrative use case, where we generated linguistic descriptions of weather maps for specific geographical expressions. These were used in a task-based evaluation to determine how well eographical expressions grounded on the models.
Original languageEnglish
Pages (from-to)970 - 983
Number of pages14
JournalInternational Journal of Computational Intelligence Systems
Issue number2
Early online date12 Sep 2019
Publication statusPublished - 2019


  • natural language generation
  • linguistic descriptions of data
  • data-to-text
  • geo-referenced data
  • language grounding
  • fuzzy sets
  • Fuzzy sets
  • Geo-referenced data
  • Data-to-text
  • Linguistic descriptions of data
  • Natural language generation
  • Language grounding


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