TAILIEUCHUNG - Báo cáo khoa học: "Lexical Disambiguation: Sources of Information and their Statistical Realization"

Lexieal disambiguation can be achieved using different sources of information. Aiming at high performance of automatic disambiguation it is important to know the relative importance and applicability of the various sources. In this paper we classify several sources of information and show how some of them can be achieved using statistical data. First evaluations indicate the extreme importance of local information, which mainly represents lexical associations and seleetional restrictions for syntactically related words. . | Lexical Disambiguation Sources of Information and their Statistical Realization Ido Dagan Computer Science Department Technion Haifa Israel and IBM Scientific Center Technion City Haifa Israel Abstract Lexical disambiguation can be achieved using different sources of information. Aiming at high performance of automatic disambiguation it is important to know the relative importance and applicability of the various sources. In this paper we classify several sources of information and show how some of them can be achieved using statistical data. First evaluations indicate the extreme importance of local information which mainly represents lexical associations and selectional restrictions for syntactically related words. 1 Disambiguation Sources The resolution of lexical ambiguities in unrestricted text is one of the most difficult tasks of natural language processing. In machine translation we are confronted with the related task of target word selection - the task of deciding which target language word is the most appropriate equivalent of a source language word in context. In contrast to computational systems humans seem to select the correct sense of an ambiguous word without much effort and usually without even being aware to the existence of an ambiguous situation. This fact naturally led researches to point out various sources of information which may provide the necessary cues for disambiguation either for humans or machines. The following paragraphs classify these sources into two major types based on either understanding of the text or frequency characteristics of it. One kind of information relates to the understanding of the meaning of the text using semantic and pragmatic knowledge and applying reasoning mechanisms. The following sentences taken from foreign news sections in the Israeli Hebrew press demonstrate how different levels of understanding can provide the disambiguating information. 1 haver ha-bayit ha- elyon shel ha parlament ha- This research .

• Báo cáo khoa học
• Lexical Disambiguation
• Sources of Information
• their Statistical Realization
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Word Sense Disambiguation
• lexical cohesion in the context
• Dongqiang Yang
• Combining Unsupervised
• Lexical Knowledge Methods
• scientific reports
• model language
• process natural language
• Constraint Handling In Prolog
• Long Papers
• 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