Chinese Organization Name Recognition Using Chunk Analysis

PACLIC 20 / Wuhan, China / 1-3 November, 200

Chinese Semantic Class Learning from Web Based on Concept-Level Characteristics

PACLIC 23 / City University of Hong Kong / 3-5 December 200

Chinese Organization Name Recognition Using Chunk Analysis

Abstract. A simplified N-best cascade model is put forward about Chinese organization names automatic recogni-tion. This model can do words segmentation, part-of-speech tag, chunks analysis and Chinese organization names recognition. The N-best cascade method can limit not only the errors propagation but also the search space. In the experiments, we integrate heuristic information and Organization name abbreviations processing into the model to achieve the better experiment results. The last precision and recall of Chinese organization names recognition are 92.31 % and 81.01 % in IEER99 newswire test set