Name
Title | ||
|---|---|---|
Unsupervised named entity recognition using syntactic and semantic contextual evidence |
Abstract | ||
|---|---|---|
Proper nouns form an open class, making the incompleteness of manually or automatically learned classification rules an obvious problem. The purpose of this paper is twofold: first, to suggest the use of a complementary "backup" method to increase the robustness of any hand-crafted or machine-learning-based NE tagger; and second, to explore the effectiveness of using more fine-grained evidence--namely, syntactic and semantic contextual knowledge---in classifying NEs. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1162/089120101300346822 | Computational Linguistics |
Keywords | Field | DocType |
classifying nes,semantic contextual knowledge,open class,machine-learning-based ne tagger,obvious problem,entity recognition,proper noun,fine-grained evidence,semantic contextual evidence,classification rule,noun,machine learning | Computer science,Computational linguistics,Robustness (computer science),Speech recognition,Corpus analysis,Natural language processing,Artificial intelligence,Named-entity recognition,Syntax,Proper noun,Backup,Applied linguistics | Journal |
Volume | Issue | ISSN |
27 | 1 | 0891-2017 |
Citations | PageRank | References |
22 | 0.90 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alessandro Cucchiarelli | 1 | 226 | 36.38 |
| paola velardi | 2 | 1553 | 163.66 |