A Large-Scale Exploration of Effective Global Features for a Joint Entity Detection and Tracking Model

Details A Large-Scale Exploration of Effective Global Features for a Joint Entity Detection and Tracking Model A Large-Scale Exploration of Effective Global Features for a Joint Entity Detection and Tracking Model

2009-07-04

arxiv.org/abs/0907.0807v1

HLT/EMNLP 2005

Computer Science

Computation and Language

Scientific paper

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.

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