Name
Abstract | ||
|---|---|---|
We present a system for identifying and tracking named, nominal, and pronominal mentions of entities within a text document. Our maximum entropy model for mention detection combines two pre-existing named entity taggers (built to extract different entity categories) and other syntactic and morphological feature streams to achieve competitive performance. We developed a novel maximum entropy model for tracking all mentions of an entity within a document. We participated in the Automatic Content Extraction (ACE) evaluation and performed well. We describe our system and present results of the ACE evaluation. |
Year | Venue | DocType |
|---|---|---|
2003 | HLT-NAACL | Conference |
Citations | PageRank | References |
2 | 1.02 | 3 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abraham Ittycheriah | 1 | 534 | 61.23 |
| Lucian Vlad Lita | 2 | 161 | 16.92 |
| Nanda Kambhatla | 3 | 390 | 51.52 |
| Nicolas Nicolov | 4 | 400 | 76.27 |
| Salim Roukos | 5 | 6248 | 845.50 |
| Margo Stys | 6 | 22 | 2.04 |