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
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
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.
Lost in Discussion? Tracking Opinion Groups in Complex Political Discussions by the Example of the FOMC Meeting Transcriptions
Cäcilia Zirn | Robert Meusel | Heiner Stuckenschmidt
Proceedings of the International Conference Recent Advances in Natural Language Processing
- Julian Seitner 1
- Christian Bizer 1
- Kai Eckert 1
- Stefano Faralli 1
- Heiko Paulheim 1
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