Statistical Sentence Condensation using Ambiguity Packing and Stochastic Disambiguation Methods for Lexical-Functional Grammar

S. Riezler, Tracy Holloway King, Dick Crouch, A. Zaenen
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引用次数: 100

Abstract

We present an application of ambiguity packing and stochastic disambiguation techniques for Lexical-Functional Grammars (LFG) to the domain of sentence condensation. Our system incorporates a linguistic parser/generator for LFG, a transfer component for parse reduction operating on packed parse forests, and a maximum-entropy model for stochastic output selection. Furthermore, we propose the use of standard parser evaluation methods for automatically evaluating the summarization quality of sentence condensation systems. An experimental evaluation of summarization quality shows a close correlation between the automatic parse-based evaluation and a manual evaluation of generated strings. Overall summarization quality of the proposed system is state-of-the-art, with guaranteed grammaticality of the system output due to the use of a constraint-based parser/generator.
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基于歧义包装和随机消歧方法的词汇功能语法统计句子凝聚
本文提出了一种基于语义功能语法的歧义填充和随机消歧技术在句子凝聚领域的应用。我们的系统包含一个用于LFG的语言解析器/生成器,一个用于在打包解析森林上操作的解析缩减的传输组件,以及一个用于随机输出选择的最大熵模型。此外,我们提出使用标准解析器评估方法来自动评估句子浓缩系统的摘要质量。摘要质量的实验评估表明,自动基于解析的评估与人工对生成字符串的评估之间存在密切的相关性。所建议系统的总体摘要质量是最先进的,由于使用了基于约束的解析器/生成器,因此保证了系统输出的语法性。
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