TAILIEUCHUNG - Báo cáo khoa học: "INTERLEAVING SYNTAX AND SEMANTICS AN EFFICIENT BOTTOM-UP PARSER*"

We describe an efficient bottom-up parser that interleaves syntactic and semantic structure building. Two techniques are presented for reducing search by reducing local ambiguity: Limited leftcontext constraints are used to reduce local syntactic ambiguity, and deferred sortal-constraint application is used to reduce local semantic ambiguity. We experimentally evaluate these techniques, and show dramatic reductions in both number of chart edges and total parsing time. | INTERLEAVING SYNTAX AND SEMANTICS IN AN EFFICIENT BOTTOM-UP PARSER John Dowding Robert Moore Frangois Andry Ị and Douglas Moran SRI International 333 Ravenswood Avenue Menlo Park CA 94025 dowding bmoore andry mor an @ ai. sri. com Abstract We describe an efficient bottom-up parser that interleaves syntactic and semantic structure building. Two techniques are presented for reducing search by reducing local ambiguity Limited leftcontext constraints are used to reduce local syntactic ambiguity and deferred sortal-constraint application is used to reduce local semantic ambiguity. We experimentally evaluate these techniques and show dramatic reductions in both number of chart edges and total parsing time. The robust processing capabilities of the parser are demonstrated in its use in improving the accuracy of a speech recognizer. INTRODUCTION The parsing problem is typically framed as a recognition problem Given a grammar and a word string determine if the word string is a member of the language described by the grammar. For some applications notably robust natural-language processing and spoken-language understanding this is insufficient since many utterances will not be accepted by the grammar because of nonstandard language inadequate grammatical coverage or errors made in speech recognition. In these cases it is still desirable to determine what well-formed phrases occurred in the word string even when the entire string is not recognized. The goal of the parser described here is to construct a chart as efficiently as possible that contains all the syntactically well-formed semantically meaningful phrases This research was supported by the Advanced Research Projects Agency under Contract ONR N00014-90-C-0085 with the Office of Naval Research. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies either expressed or implied of the Advanced Research Projects Agency .

• Báo cáo khoa học
• INTERLEAVING SYNTAX
• SEMANTICS AN EFFICIENT BOTTOM UP PARSER
• John Dowding
• 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