Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
Readings in uncertain reasoning
Blocking Gibbs sampling in very large probabilistic expert systems
International Journal of Human-Computer Studies - Special issue: real-world applications of uncertain reasoning
Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Constructing Biological Knowledge Bases by Extracting Information from Text Sources
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
Kernel methods for relation extraction
The Journal of Machine Learning Research
Gene name identification and normalization using a model organism database
Journal of Biomedical Informatics - Special issue: Named entity recognition in biomedicine
Joint deduplication of multiple record types in relational data
Proceedings of the 14th ACM international conference on Information and knowledge management
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Contrastive estimation: training log-linear models on unlabeled data
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Autonomously semantifying wikipedia
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Freebase: a collaboratively created graph database for structuring human knowledge
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
Learning and inference with constraints
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Unsupervised constraint driven learning for transliteration discovery
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Latent variable perceptron algorithm for structured classification
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
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
Generalized expectation criteria for bootstrapping extractors using record-text alignment
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Constraint-driven rank-based learning for information extraction
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Collective cross-document relation extraction without labelled data
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Scalable knowledge harvesting with high precision and high recall
Proceedings of the fourth ACM international conference on Web search and data mining
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
End-to-end relation extraction using distant supervision from external semantic repositories
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Structured relation discovery using generative models
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Improving distantly supervised extraction of drug-drug and protein-protein interactions
ROBUS-UNSUP '12 Proceedings of the Joint Workshop on Unsupervised and Semi-Supervised Learning in NLP
Towards automatic construction of knowledge bases from Chinese online resources
ACL '12 Proceedings of ACL 2012 Student Research Workshop
Temporally anchored relation extraction
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Reducing wrong labels in distant supervision for relation extraction
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Big data versus the crowd: looking for relationships in all the right places
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Linking named entities to any database
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Multi-instance multi-label learning for relation extraction
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Open language learning for information extraction
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Weakly supervised training of semantic parsers
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
New resources and perspectives for biomedical event extraction
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
Relabeling distantly supervised training data for temporal knowledge base population
AKBC-WEKEX '12 Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction
Adding distributional semantics to knowledge base entities through web-scale entity linking
AKBC-WEKEX '12 Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction
Probabilistic databases of universal schema
AKBC-WEKEX '12 Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction
Identifying untyped relation mentions in a corpus given an ontology
TextGraphs-7 '12 Workshop Proceedings of TextGraphs-7 on Graph-based Methods for Natural Language Processing
Crosslingual distant supervision for extracting relations of different complexity
Proceedings of the 21st ACM international conference on Information and knowledge management
Knowledge harvesting in the big-data era
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Extracting meronyms for a biology knowledge base using distant supervision
Proceedings of the 2013 workshop on Automated knowledge base construction
A survey of noise reduction methods for distant supervision
Proceedings of the 2013 workshop on Automated knowledge base construction
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Several recent works on relation extraction have been applying the distant supervision paradigm: instead of relying on annotated text to learn how to predict relations, they employ existing knowledge bases (KBs) as source of supervision. Crucially, these approaches are trained based on the assumption that each sentence which mentions the two related entities is an expression of the given relation. Here we argue that this leads to noisy patterns that hurt precision, in particular if the knowledge base is not directly related to the text we are working with. We present a novel approach to distant supervision that can alleviate this problem based on the following two ideas: First, we use a factor graph to explicitly model the decision whether two entities are related, and the decision whether this relation is mentioned in a given sentence; second, we apply constraint-driven semi-supervision to train this model without any knowledge about which sentences express the relations in our training KB. We apply our approach to extract relations from the New York Times corpus and use Freebase as knowledge base. When compared to a state-of-the-art approach for relation extraction under distant supervision, we achieve 31% error reduction.