Proceedings of the AAAI 2009 Spring Symposium on Learning by Reading and Learning to Read

Cross-Document Coreference Resolution: A Key Technology for Learning by Reading

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Automatic knowledge base population from text is an important technology for a broad range of approaches to learning by reading. Effective automated knowledge base population depends critically upon coreference resolution of entities across sources. Use of a wide range of features, both those that capture evidence for entity merging and those that argue against merging, can significantly improve machine learning-based cross-document coreference resolution. Results from the Global Entity Detection and Recognition task of the NIST Automated Content Extraction (ACE) 2008 evaluation support this conclusion.

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information extraction, language, natural language processing


AAAI Press

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