Freepal: A Large Collection of Deep Lexico-Syntactic Patterns for Relation Extraction

Johannes Kirschnick, Alan Akbik, Holmer Hemsen

Abstract
The increasing availability and maturity of both scalable computing architectures and deep syntactic parsers is opening up new possibilities for Relation Extraction (RE) on large corpora of natural language text. In this paper, we present Freepal, a resource designed to assist with the creation of relation extractors for more than 5,000 relations defined in the Freebase knowledge base (KB). The resource consists of over 10 million distinct lexico-syntactic patterns extracted from dependency trees, each of which is assigned to one or more Freebase relations with different confidence strengths. We generate the resource by executing a large-scale distant supervision approach on the ClueWeb09 corpus to extract and parse over 260 million sentences labeled with Freebase entities and relations. We make Freepal freely available to the research community, and present a web demonstrator to the dataset, accessible from free-pal.appspot.com.
Anthology ID:
L14-1595
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
2071–2075
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/764_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Johannes Kirschnick, Alan Akbik, and Holmer Hemsen. 2014. Freepal: A Large Collection of Deep Lexico-Syntactic Patterns for Relation Extraction. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 2071–2075, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Freepal: A Large Collection of Deep Lexico-Syntactic Patterns for Relation Extraction (Kirschnick et al., LREC 2014)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/764_Paper.pdf
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