Relational Recognition for Information Extraction in Free Text Documents

Erik J. Larson and Todd C. Hughes

Information extraction tools provide an important means for distilling content from free text documents, and knowledge-based tools provide an important means for automatically reasoning over statements expressed as well-formed tuples. A number of techniques deliver reliable extraction of entities, less reliable extraction of relations, and poor extraction on entity-entity-relation tuples. However, tuple extraction is needed to bridge the gap between free text and knowledge-based applications. We describe an information extraction system and experiment that demonstrates accurate tuple extraction in a selected domain.


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