Description of the NTU System used for MET-2.
Hsin‐Hsi Chen, Yung-Wei Ding, Shih-Chung Tsai, Guo-Wei Bian · 1998
Named entities form the major components in a document. When we catch the fundamental entities, we can understand a document to some degree. This paper employs different types of information from different levels of text to extract named entities, including character conditions, statistic information, titles, punctuation marks, organization and location keywords, speech-act and locative verbs, cache and n-gram model. In the formal run of MET-2, the F-measures P&R, 2P&R and P&2R are 79.61%, 77.88% and 81.42%, respectively. INTRODUCTION People, affairs, time, places and things are five basic entities in a document. When we catch the fundamental entities, we can understand a document to some degree. Natural Language Processing Laboratory (NLPL) in Department of Computer Science and Information Engineering (CSIE), National Taiwan University (NTU) starts to study named entity extraction problem in 1993. At first, we focus on the extraction of Chinese person names, transliterated person na...