Unsupervised Named Entity Recognition Using Syntatic and Semantic Contextual Evidence

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 machinelearning-based NE tagger; and second, to explore the effectiveness of using more fine-grained evidence--namely, syntactic and semantic contextual knowledge--in classifying NEs.