Exploiting Diverse Knowledge Sources via Maximum Entropy in Named Entity Recognition

@inproceedings{Borthwick1998ExploitingDK,
  title={Exploiting Diverse Knowledge Sources via Maximum Entropy in Named Entity Recognition},
  author={Andrew Borthwick and John Sterling and Eugene Agichtein and Ralph Grishman},
  booktitle={VLC@COLING/ACL},
  year={1998}
}
This paper describes a novel statistical namedentity (i.e. "proper name") recognition system built around a maximum entity framework. By working v,ithin the framework of maximum entropy theory and utilizing a flexible object-based architecture, the system is able to make use of an extraordinarily diverse range of knowledge sources in making its tagging decisions. These knowledge sources include capitalization features, lexical features, features indicating the current section of text (i.e… CONTINUE READING
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