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ReqTagger: A rule-based tagger for automatic Glossary of Terms extraction from ontology requirements


[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication


Published in

Foundations of Computing and Decision Sciences

Journal year: 2022 | Journal volume: vol. 47 | Journal number: no. 1

Article type

scientific article

Publication language


  • Competency Questions
  • Ontology Requirements
  • Ontology
  • Information Extraction
  • Part-of-Speech tagging

EN Glossary of Terms extraction from textual requirements is an impor- tant step in ontology engineering methodologies. Although initially it was intended to be performed manually, last years have shown that some degree of automatization is possible. Based on these promising approaches, we introduce a novel, human inter- pretable, rule-based method named ReqTagger, which can extract candidates for ontology entities (classes or instances) and relations (data or object properties) from textual requirements automatically. We compare ReqTagger to existing automatic methods on an evaluation benchmark consisting of over 550 requirements and tagged with over 1700 entities and relations expected to be extracted. We discuss the quality of ReqTagger and provide details showing why it outperforms other methods. We also publish both the evaluation dataset and the implementation of ReqTagger.

Date of online publication


Pages (from - to)

65 - 86




License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Points of MNiSW / journal


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