Abstract:

Based on the research issue of sense guessing of Chinese unknown words, different levels of semantic dictionary were introduced by applying “Semantic Knowledge-base of Modern Chinese”. Models have constructed for sense guessing by using these dictionary. Each model was intergrated to predict the unknown words and obtained better performance. Based on each model, semantic prediction and annotation of the unknown words in People’s Daily which published in 2000 were evaluated. Finally, corpus resources with the sense annotation of unknown words were obtained.

Key words: Chinese unknown words, sense guessing, semantic annotation, ensemble learning

摘要：

基于《现代汉语语义词典》, 首先建立不同语义层次的词典, 根据词典分别构建模型并进行语义预测, 然后将各个模型进行集成, 通过集成模型再对未登录词进行语义预测, 得到较好的预测性能。利用预测模型对2000年《人民日报》语料进行未登录词语义预测和标注, 最终得到带有未登录词语义义项标注的语料资源。

关键词: 汉语未登录词, 语义预测, 语义标注, 集成学习