Open information extraction from the web
Communications of the ACM - Surviving the data deluge
Collective annotation of Wikipedia entities in web text
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
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
Unsupervised techniques for discovering ontology elements from Wikipedia article links
FAM-LbR '10 Proceedings of the NAACL HLT 2010 First International Workshop on Formalisms and Methodology for Learning by Reading
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We present techniques for uncovering links between terror incidents, organizations, and people involved with these incidents. Our methods involve performing shallow NLP tasks to extract entities of interest from documents and using linguistic pattern matching and filtering techniques to assign specific relations to the entities discovered. We also gather more information about these entities from the Linked Open Data Cloud, and further allow human analysts to add intelligent inference rules appropriate to the domain. All this information is integrated in a knowledge base in the form of a graph that maintains the semantics between different types of nodes involved in the graph. This knowledge base can then be queried by the analysts to create actionable intelligence.