Paper Info
Title
A Large DataBase of Hypernymy Relations Extracted from the Web.
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.
Year
Venue
Keywords
2016
LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
Hearst patterns,hypernym extraction,big data,Web crawling,Application Programming Interface
Field
DocType
Citations 
World Wide Web,Computer science,Natural language processing,Artificial intelligence,Database
Conference
12
PageRank 
References 
Authors
0.59
17
7
Name
Order
Citations
PageRank
Julian Seitner1120.59
Christian Bizer28448524.93
Kai Eckert315023.67
stefano faralli430126.70
Robert Meusel523416.62
Heiko Paulheim6109584.19
Simone Paolo Ponzetto72280129.35