Scaling question answering to the web
ACM Transactions on Information Systems (TOIS)
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Survey of the Message Understanding Conferences
HLT '93 Proceedings of the workshop on Human Language Technology
Inductive Dependency Parsing (Text, Speech and Language Technology)
Inductive Dependency Parsing (Text, Speech and Language Technology)
On-demand information extraction
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Learning to link with wikipedia
Proceedings of the 17th ACM conference on Information and knowledge management
The YAGO-NAGA approach to knowledge discovery
ACM SIGMOD Record
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
TextRunner: open information extraction on the web
NAACL-Demonstrations '07 Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Exploring content models for multi-document summarization
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Open information extraction from the web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Answering web questions using structured data: dream or reality?
Proceedings of the VLDB Endowment
Distant supervision for relation extraction without labeled data
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Relational duality: unsupervised extraction of semantic relations between entities on the web
Proceedings of the 19th international conference on World wide web
Open information extraction using Wikipedia
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Learning 5000 relational extractors
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Learning arguments and supertypes of semantic relations using recursive patterns
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Knowledge-based weak supervision for information extraction of overlapping relations
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A Bayesian model for unsupervised semantic parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Relation extraction with relation topics
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Structured relation discovery using generative models
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Identifying relations for open information extraction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Feature-based models for improving the quality of noisy training data for relation extraction
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
A survey of noise reduction methods for distant supervision
Proceedings of the 2013 workshop on Automated knowledge base construction
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We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant supervision using relations from the knowledge base FreeBase, but do not require any manual heuristic nor manual seed list selections. Results show that the learned patterns can be used to extract new relations with good precision.