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Glossary of Terms extraction from textual requirements is an important 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 interpretable, rule-based method named R eq T agger , which can extract candidates for ontology entities (classes or instances) and relations (data or object properties) from textual requirements automatically. We compare R eq T agger  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 R eq T agger  and provide details showing why it outperforms other methods. We also publish both the evaluation dataset and the implementation of R eq T agger .

ReqTagger: A Rule-Based Tagger for Automatic Glossary of Terms Extraction from Ontology Requirements