@InProceedings{daume05coref,
  author =       {Hal {Daum\'e III} and Daniel Marcu},
  title =        {A Large-Scale Exploration of Effective Global Features for a Joint Entity Detection and Tracking Model},
  booktitle =    {Joint Conference on Human Language Technology and Empirical Methods in Natural Language Processing (HLT/EMNLP)},
  year =         {2005},
  address =      {Vancouver, Canada},
  abstract =     {
    Entity detection and tracking (EDT) is the task of identifying textual
    mentions of real-world entities in documents, extending the named
    entity detection and coreference resolution task by considering
    mentions other than names (pronouns, definite descriptions, etc.).
    Like NE tagging and coreference resolution, most solutions to the EDT
    task separate out the mention detection aspect from the coreference
    aspect.  By doing so, these solutions are limited to using only local
    features for learning.  In contrast, by modeling both aspects of the
    EDT task simultaneously, we are able to learn using highly complex,
    non-local features.  We develop a new joint EDT model and explore the
    utility of many features, demonstrating their effectiveness on this
    task.
  },
  url = {http://pub.hal3.name/#daume05coref}
}