Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Extracting Patterns and Relations from the World Wide Web
WebDB '98 Selected papers from the International Workshop on The World Wide Web and Databases
Towards the self-annotating web
Proceedings of the 13th international conference on World Wide Web
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Unsupervised named-entity extraction from the web: an experimental study
Artificial Intelligence
Espresso: leveraging generic patterns for automatically harvesting semantic relations
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
A probabilistic model of redundancy in information extraction
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Ontology-driven, unsupervised instance population
Web Semantics: Science, Services and Agents on the World Wide Web
Using the Web to Reduce Data Sparseness in Pattern-Based Information Extraction
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
SOFIE: a self-organizing framework for information extraction
Proceedings of the 18th international conference on World wide web
Information Extraction and Semantic Annotation of Wikipedia
Proceedings of the 2008 conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Learning web query patterns for imitating Wikipedia articles
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Using graph based method to improve bootstrapping relation extraction
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
Using the web to validate lexico-semantic relations
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
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Several bootstrapping-based relation extraction algorithms working on large corpora or on the Web have been presented in the literature. A crucial issue for such algorithms is to avoid the introduction of too much noise into further iterations. Typically, this is achieved by applying appropriate pattern and tuple evaluation measures, henceforth called filtering functions, thereby selecting only the most promising patterns and tuples. In this paper, we systematically compare different filtering functions proposed across the literature. Although we also discuss our own implementation of a pattern learning algorithm, the main contribution of the paper is actually the extensive comparison and evaluation of the different filtering functions proposed in the literature with respect to seven datasets. Our results indicate that some of the commonly used filters do not outperform a trivial baseline filter in a statistically significant manner.