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
Scenario customization for information extraction
Scenario customization for information extraction
On building a more efficient grammar by exploiting types
Natural Language Engineering
A compact architecture for dialogue management based on scripts and meta-outputs
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
An improved extraction pattern representation model for automatic IE pattern acquisition
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Counter-training in discovery of semantic patterns
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Task Driven Coreference Resolution for Relation Extraction
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
The Stanford typed dependencies representation
CrossParser '08 Coling 2008: Proceedings of the workshop on Cross-Framework and Cross-Domain Parser Evaluation
Improving semi-supervised acquisition of relation extraction patterns
IEBeyondDoc '06 Proceedings of the Workshop on Information Extraction Beyond The Document
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
Learning arguments and supertypes of semantic relations using recursive patterns
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Boosting relation extraction with limited closed-world knowledge
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Analysis and improvement of minimally supervised machine learning for relation extraction
NLDB'09 Proceedings of the 14th international conference on Applications of Natural Language to Information Systems
Large-Scale learning of relation-extraction rules with distant supervision from the web
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
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The paper describes the operation and evolution of a linguistically oriented framework for the minimally supervised learning of relation extraction grammars from textual data. Cornerstones of the approach are the acquisition of extraction rules from parsing results, the utilization of closed-world semantic seeds and a filtering of rules and instances by confidence estimation. By a systematic walk through the major challenges for this approach the obtained results and insights are summarized. Open problems are addressed and strategies for solving these are outlined.