Publications
Authors:
  • Will Radford , Xavier Carreras , James Henderson
Citation:
EMNLP, Lisboa, Portugal, September 17-21, 2015.
Abstract:
We consider a novel setting for Named Entity Recognition (NER) where we have access to document-specific knowledge base tags. These tags consist of a canonical name from a knowledge base (KB) and entity type, but are not aligned to the text. We explore how to use KB tags to create document-specific gazetteers at inference time to improve NER. We find that this kind of supervision helps recognise organisations more than standard wide-coverage gazetteers. Moreover, augmenting document-specific gazetteers with KB information lets users specify fewer tags for the same performance, reducing cost.
Year:
2015
Report number:
2015/042
Attachments: