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

1 Citation (Scopus)
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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 Sept 2019
Publication statusPublished - 2019

Bibliographical note

Jose M. Alonso is Ramon y Cajal Researcher (RYC-2016-19802). This research was also funded by the Spanish Ministry of Science, Innovation and Universities (grants RTI2018-099646-BI00, TIN2017-84796-C2-1-R and TIN2017-90773-REDT) and the Galician Ministry of Education, University and Professional Training (grants ED431F2018/02, ED431C 2018/29 and “accreditation 2016-2019, ED431G/08”). All grants were co-funded by the European Regional Development Fund
(ERDF/FEDER program).


  • 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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