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 journalArticle

Abstract

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
Volume12
Issue number2
Early online date12 Sep 2019
DOIs
Publication statusPublished - 2019

Fingerprint

Electric grounding
Linguistics

Keywords

  • 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

ASJC Scopus subject areas

  • Computational Mathematics
  • Computer Science(all)

Cite this

Fuzzy-Based Language Grounding of Geographical References : From Writers to Readers. / Ramos, Alejandro ; Alonso, Jose M. (Corresponding Author); Reiter, Ehud; Van Deemter, Kees; Gatt, Albert.

In: International Journal of Computational Intelligence Systems, Vol. 12, No. 2, 2019, p. 970 - 983.

Research output: Contribution to journalArticle

@article{8ac3a26999b345faa11c50b990c74168,
title = "Fuzzy-Based Language Grounding of Geographical References: From Writers to Readers",
abstract = "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.",
keywords = "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",
author = "Alejandro Ramos and Alonso, {Jose M.} and Ehud Reiter and {Van Deemter}, Kees and Albert Gatt",
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).",
year = "2019",
doi = "10.2991/ijcis.d.190826.002",
language = "English",
volume = "12",
pages = "970 -- 983",
journal = "International Journal of Computational Intelligence Systems",
issn = "1875-6891",
publisher = "Atlantis Press SARL",
number = "2",

}

TY - JOUR

T1 - Fuzzy-Based Language Grounding of Geographical References

T2 - From Writers to Readers

AU - Ramos, Alejandro

AU - Alonso, Jose M.

AU - Reiter, Ehud

AU - Van Deemter, Kees

AU - Gatt, Albert

N1 - 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).

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - natural language generation

KW - linguistic descriptions of data

KW - data-to-text

KW - geo-referenced data

KW - language grounding

KW - fuzzy sets

KW - Fuzzy sets

KW - Geo-referenced data

KW - Data-to-text

KW - Linguistic descriptions of data

KW - Natural language generation

KW - Language grounding

UR - http://www.scopus.com/inward/record.url?scp=85074652955&partnerID=8YFLogxK

U2 - 10.2991/ijcis.d.190826.002

DO - 10.2991/ijcis.d.190826.002

M3 - Article

VL - 12

SP - 970

EP - 983

JO - International Journal of Computational Intelligence Systems

JF - International Journal of Computational Intelligence Systems

SN - 1875-6891

IS - 2

ER -