A Large DataBase of Hypernymy Relations Extracted from the Web.

Julian Seitner, Christian Bizer, Kai Eckert, Stefano Faralli, Robert Meusel, Heiko Paulheim, Simone Paolo Ponzetto

Abstract
Hypernymy relations (those where an hyponym term shares a “isa” relationship with his hypernym) play a key role for many Natural Language Processing (NLP) tasks, e.g. ontology learning, automatically building or extending knowledge bases, or word sense disambiguation and induction. In fact, such relations may provide the basis for the construction of more complex structures such as taxonomies, or be used as effective background knowledge for many word understanding applications. We present a publicly available database containing more than 400 million hypernymy relations we extracted from the CommonCrawl web corpus. We describe the infrastructure we developed to iterate over the web corpus for extracting the hypernymy relations and store them effectively into a large database. This collection of relations represents a rich source of knowledge and may be useful for many researchers. We offer the tuple dataset for public download and an Application Programming Interface (API) to help other researchers programmatically query the database.
Anthology ID:
L16-1056
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
360–367
Language:
URL:
https://aclanthology.org/L16-1056
DOI:
Bibkey:
Cite (ACL):
Julian Seitner, Christian Bizer, Kai Eckert, Stefano Faralli, Robert Meusel, Heiko Paulheim, and Simone Paolo Ponzetto. 2016. A Large DataBase of Hypernymy Relations Extracted from the Web.. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 360–367, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
A Large DataBase of Hypernymy Relations Extracted from the Web. (Seitner et al., LREC 2016)
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https://preview.aclanthology.org/add_acl24_videos/L16-1056.pdf
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