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

and

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.


  • 339771 bytes

information extraction, language, natural language processing

InProceedings

AAAI Press

Downloads: 2504 downloads

Google Scholar Citations: 6 citations

UMBC ebiquity