TAILIEUCHUNG - Báo cáo khoa học: "Inducing Gazetteers for Named Entity Recognition by Large-scale Clustering of Dependency Relations"

We propose using large-scale clustering of dependency relations between verbs and multiword nouns (MNs) to construct a gazetteer for named entity recognition (NER). Since dependency relations capture the semantics of MNs well, the MN clusters constructed by using dependency relations should serve as a good gazetteer. However, the high level of computational cost has prevented the use of clustering for constructing gazetteers. | Inducing Gazetteers for Named Entity Recognition by Large-scale Clustering of Dependency Relations Jun ichi Kazama Japan Advanced Institute of Science and Technology JAIST Asahidai 1-1 Nomi Ishikawa 923-1292 Japan kazama@ Kentaro Torisawa National Institute of Information and Communications Technology NICT 3-5 Hikaridai Seika-cho Soraku-gun Kyoto 619-0289 Japan torisawa@ Abstract We propose using large-scale clustering of dependency relations between verbs and multiword nouns MNs to construct a gazetteer for named entity recognition NER . Since dependency relations capture the semantics of MNs well the MN clusters constructed by using dependency relations should serve as a good gazetteer. However the high level of computational cost has prevented the use of clustering for constructing gazetteers. We parallelized a clustering algorithm based on expectationmaximization EM and thus enabled the construction of large-scale MN clusters. We demonstrated with the IREX dataset for the Japanese NER that using the constructed clusters as a gazetteer cluster gazetteer is a effective way of improving the accuracy of NER. Moreover we demonstrate that the combination of the cluster gazetteer and a gazetteer extracted from Wikipedia which is also useful for NER can further improve the accuracy in several cases. 1 Introduction Gazetteers or entity dictionaries are important for performing named entity recognition NER accurately. Since building and maintaining high-quality gazetteers by hand is very expensive many methods have been proposed for automatic extraction of gazetteers from texts Riloff and Jones 1999 Thelen and Riloff 2002 Etzioni et al. 2005 Shinzato et al. 2006 Talukdar et al. 2006 Nadeau et al. 2006 . Most studies using gazetteers for NER are based on the assumption that a gazetteer is a mapping from a multi-word noun MN 1 to named entity categories such as Tokyo Stock Exchange ORGANIZATION .2 However since the correspondence between the labels and

• Báo cáo khoa học
• Inducing Gazetteers
• Named Entity Recognition
• Large scale Clustering
• Dependency Relations
• báo cáo khoa học
• báo cáo ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Bài giảng Xử lý ngôn ngữ tự nhiên
• Ngôn ngữ tự nhiên
• Kỹ thuật lập trình
• Xử lý nhập nhằng ngữ nghĩa
• Xử lý ngữ nghĩa
• Xử lý ngôn ngữ
• Natural Language Processing
• Ngôn ngữ lập trình
• Nhập nhằng cấu trúc
• Tri thức về ngôn ngữ
• Mô hình ngôn ngữ
• Mô hình n gram
• Dịch máy
• Phương pháp dịch máy
• Hiểu ngôn ngữ
• Phân tích ngữ nghĩa
• Phân loại tin tự động
• Biểu diễn vị từ
• Thuộc tính về sự kiện
• Thuộc tính về sự kiện
• Mô hình ngôn ngữ Google Book N grams
• Mô hình ngôn ngữ KenLM
• Phương pháp làm mịn
• Tách từ tiếng Việt
• Gán nhãn từ loại
• Phân tích cú pháp
• Nghĩa từ vựng
• Phân giải nhập nhằng từ
• Phân loại văn bản
• Lexical chain
• Phản hồi thông tin
• Bài toán PTCP
• Cấu trúc ngữ pháp
• Phân tích cú pháp xác suất
• CKY kết hợp xác suất
• Văn phạm phi ngữ cảnh xác suất
• Hình thái học