文章基本信息

标题：Unsupervised Named Entity Recognition Using Syntactic and Semantic Contextual Evidence
本地全文：下载
作者：Alessandro Cucchiarelli ; Paola Velardi
期刊名称：Computational Linguistics
印刷版ISSN：0891-2017
电子版ISSN：1530-9312
出版年度：2001
卷号：27
期号：1
页码：123-131
DOI：10.1162/089120101300346822
语种：English
出版社：MIT Press
摘要：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.