TAILIEUCHUNG - Báo cáo khoa học: "Inducing German Semantic Verb Classes from Purely Syntactic Subcategorisation Information"

The paper describes the application of kMeans, a standard clustering technique, to the task of inducing semantic classes for German verbs. Using probability distributions over verb subcategorisation frames, we obtained an intuitively plausible clustering of 57 verbs into 14 classes. The automatic clustering was evaluated against independently motivated, handconstructed semantic verb classes. A series of post-hoc cluster analyses explored the influence of specific frames and frame groups on the coherence of the verb classes, and supported the tight connection between the syntactic behaviour of the verbs and their lexical meaning components. . | Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics ACL Philadelphia July 2002 pp. 223-230. Inducing German Semantic Verb Classes from Purely Syntactic Subcategorisation Information Sabine Schulte im Walde Chris Brew Institut fur Maschinelle Sprachverarbeitung Department of Linguistics Universitat Stuttgart The Ohio State University AzenbergstraBe 12 70174 Stuttgart Germany Columbus USA OH 43210-1298 schulte@ cbrew@ Abstract The paper describes the application of k-Means a standard clustering technique to the task of inducing semantic classes for German verbs. Using probability distributions over verb subcategorisation frames we obtained an intuitively plausible clustering of 57 verbs into 14 classes. The automatic clustering was evaluated against independently motivated hand-constructed semantic verb classes. A series of post-hoc cluster analyses explored the influence of specific frames and frame groups on the coherence of the verb classes and supported the tight connection between the syntactic behaviour of the verbs and their lexical meaning components. 1 Introduction A long-standing linguistic hypothesis asserts a tight connection between the meaning components of a verb and its syntactic behaviour To a certain extent the lexical meaning of a verb determines its behaviour particularly with respect to the choice of its arguments. The theoretical foundation has been established in extensive work on semantic verb classes such as Levin 1993 for English and Vázquez et al. 2000 for Spanish each verb class contains verbs which are similar in their meaning and in their syntactic properties. From a practical point of view a verb classification supports Natural Language Processing tasks since it provides a principled basis for filling gaps in available lexical knowledge. For example the English verb classification has been used for applications such as machine translation Dorr 1997 word sense .

• Báo cáo khoa học
• Inducing German Semantic Verb Classes
• Purely Syntactic Subcategorisation Information
• Sabine Schulte
• báo cáo khoa học
• mô hình 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 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