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Machine Learning for Named Entity Recognition


The SEER project was intended to extend and generalise the state-of-the-art in entity recognition so that it could become a reliable enabling technology for a wide range of applications and higher-level NLP tasks. Our goal was to develop the means to recognize and classify a much wider range of entities than are traditionally treated, and to develop techniques which can be applied in a wide range of text types.

Rapid adaptation to new domains was a priority and this required modularity in the processing pipeline as well as the innovative use of machine-learning techniques to enable the use of unnannotated corpora as training material wherever possible.

Funding Agency

Edinburgh-Stanford Link


University of Edinburgh University of Edinburgh

Stanford University

Start Date: 01 January 2002
End Date: 30 December 2004
Last modified 2006-07-19 06:12 PM