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

No. 7: Learning by Reading and Learning to Read

Volume

Papers from the 2009 AAAI Spring Symposium

Contents

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.