TAILIEUCHUNG - Báo cáo khoa học: "An Improved Redundancy Elimination Algorithm for Underspecified Representations"

We present an efficient algorithm for the redundancy elimination problem: Given an underspecified semantic representation (USR) of a scope ambiguity, compute an USR with fewer mutually equivalent readings. The algorithm operates on underspecified chart representations which are derived from dominance graphs; it can be applied to the USRs computed by large-scale grammars. We evaluate the algorithm on a corpus, and show that it reduces the degree of ambiguity significantly while taking negligible runtime. . | An Improved Redundancy Elimination Algorithm for Underspecified Representations Alexander Koller and Stefan Thater Dept. of Computational Linguistics Universitat des Saarlandes Saarbrucken Germany koller stth @ Abstract We present an efficient algorithm for the redundancy elimination problem Given an underspecified semantic representation USR of a scope ambiguity compute an USR with fewer mutually equivalent readings. The algorithm operates on underspecified chart representations which are derived from dominance graphs it can be applied to the USRs computed by large-scale grammars. We evaluate the algorithm on a corpus and show that it reduces the degree of ambiguity significantly while taking negligible runtime. 1 Introduction Underspecification is nowadays the standard approach to dealing with scope ambiguities in computational semantics van Deemter and Peters 1996 Copestake et al. 2004 Egg et al. 2001 Blackburn and Bos 2005 . The basic idea behind it is to not enumerate all possible semantic representations for each syntactic analysis but to derive a single compact underspecified representation USR . This simplifies semantics construction and current algorithms support the efficient enumeration of the individual semantic representations from an USR Koller and Thater 2005b . A major promise of underspecification is that it makes it possible in principle to rule out entire subsets of readings that we are not interested in wholesale without even enumerating them. For instance real-world sentences with scope ambiguities often have many readings that are semantically equivalent. Subsequent modules . for doing inference will typically only be interested in one reading from each equivalence class and all others could be deleted. This situation is illustrated by the following two out of many sentences from the Rondane treebank which is distributed with the English Resource Grammar ERG Flickinger 2002 a large-scale HPSG grammar of English. 1 For .

• Báo cáo khoa học
• An Improved Redundancy Elimination Algorithm
• Underspecified Representations
• Alexander Koller and Stefan Thater
• 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