TAILIEUCHUNG - Báo cáo khoa học: "Probabilistic disambiguation models for wide-coverage HPSG parsing"

This paper reports the development of loglinear models for the disambiguation in wide-coverage HPSG parsing. The estimation of log-linear models requires high computational cost, especially with widecoverage grammars. Using techniques to reduce the estimation cost, we trained the models using 20 sections of Penn Treebank. A series of experiments empirically evaluated the estimation techniques, and also examined the performance of the disambiguation models on the parsing of real-world sentences. . | Probabilistic disambiguation models for wide-coverage HPSG parsing Yusuke Miyao Department of Computer Science University of Tokyo Hongo 7-3-1 Bunkyo-ku Tokyo Japan yusuke@ Jun ichi Tsujii Department of Computer Science University of Tokyo Hongo 7-3-1 Bunkyo-ku Tokyo Japan CREST JST tsujii@ Abstract This paper reports the development of log-linear models for the disambiguation in wide-coverage HPSG parsing. The estimation of log-linear models requires high computational cost especially with wide-coverage grammars. Using techniques to reduce the estimation cost we trained the models using 20 sections of Penn Treebank. A series of experiments empirically evaluated the estimation techniques and also examined the performance of the disambiguation models on the parsing of real-world sentences. 1 Introduction Head-Driven Phrase Structure Grammar HPSG Pollard and Sag 1994 has been studied extensively from both linguistic and computational points of view. However despite research on HPSG processing efficiency Oepen et al. 2002a the application of HPSG parsing is still limited to specific domains and short sentences Oepen et al. 2002b Toutanova and Manning 2002 . Scaling up HPSG parsing to assess real-world texts is an emerging research field with both theoretical and practical applications. Recently a wide-coverage grammar and a large treebank have become available for English HPSG Miyao et al. 2004 . A large treebank can be used as training and test data for statistical models. Therefore we now have the basis for the development and the evaluation of statistical disambiguation models for wide-coverage HPSG parsing. The aim of this paper is to report the development of log-linear models for the disambiguation in wide-coverage HPSG parsing and their empirical evaluation through the parsing of the Wall Street Journal of Penn Treebank II Marcus et al. 1994 . This is challenging because the estimation of log-linear models is computationally

• Báo cáo khoa học
• Probabilistic disambiguation models
• wide coverage HPSG parsing
• Yusuke Miyao
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Unsupervised Sense Disambiguation
• Bilingual Probabilistic Models
• Indrajit Bhattacharya
• 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 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