Paper: A Large-Scale Exploration Of Effective Global Features For A Joint Entity Detection And Tracking Model

ACL ID H05-1013
Title A Large-Scale Exploration Of Effective Global Features For A Joint Entity Detection And Tracking Model
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005
Authors

Entity detection and tracking (EDT) is the task of identifying textual mentions of real-world entities in documents, ex- tending the named entity detection and coreference resolution task by consider- ing mentions other than names (pronouns, de nite descriptions, etc.). Like NE tag- ging and coreference resolution, most so- lutions to the EDT task separate out the mention detection aspect from the corefer- ence 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 com- plex, non-local features. We develop a new joint EDT model and explore the util- ity of many features, demonstrating their effectiveness on this task.