生成用于语法语义分析的阿拉伯语TAG

IF 2.3 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Chérifa Ben Khelil, C. Zribi, D. Duchier, Y. Parmentier
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引用次数: 0

摘要

阿拉伯语对自动加工提出了许多挑战。虽然有几项研究已经解决了一些问题,但是处理阿拉伯文的电子资源仍然相对稀少或没有广泛使用。本文提出了一种具有语法-语义接口的树相邻语法。它适用于现代标准阿拉伯语,但它可以很容易地适应其他语言。这个名为“ArabTAG V2.0”(阿拉伯树相邻语法)的语法是通过称为元语法的抽象表示半自动生成的。为了确保其开发,ArabTAG V2.0受益于使用现象语料库的语法测试环境。进一步的实验验证了该语法的覆盖范围以及语法语义分析。结果表明,ArabTAG V2.0可以覆盖大部分的句法结构和不同的语言现象,准确率达到88.76%。此外,我们能够对句子进行语义分析并构建其语义表示,准确率约为95.63%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generating Arabic TAG for syntax-semantics analysis
Arabic presents many challenges for automatic processing. Although several research studies have addressed some issues, electronic resources for processing Arabic remain relatively rare or not widely available. In this paper, we propose a Tree-adjoining grammar with a syntax-semantic interface. It is applied to the modern standard Arabic, but it can be easily adapted to other languages. This grammar named “ArabTAG V2.0” (Arabic Tree Adjoining Grammar) is semi-automatically generated by means of an abstract representation called meta-grammar. To ensure its development, ArabTAG V2.0 benefits from a grammar testing environment that uses a corpus of phenomena. Further experiments were performed to check the coverage of this grammar as well as the syntax-semantic analysis. The results showed that ArabTAG V2.0 can cover the majority of syntactical structures and different linguistic phenomena with a precision rate of 88.76%. Moreover, we were able to semantically analyze sentences and build their semantic representations with a precision rate of about 95.63%.
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来源期刊
Natural Language Engineering
Natural Language Engineering COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
5.90
自引率
12.00%
发文量
60
审稿时长
>12 weeks
期刊介绍: Natural Language Engineering meets the needs of professionals and researchers working in all areas of computerised language processing, whether from the perspective of theoretical or descriptive linguistics, lexicology, computer science or engineering. Its aim is to bridge the gap between traditional computational linguistics research and the implementation of practical applications with potential real-world use. As well as publishing research articles on a broad range of topics - from text analysis, machine translation, information retrieval and speech analysis and generation to integrated systems and multi modal interfaces - it also publishes special issues on specific areas and technologies within these topics, an industry watch column and book reviews.
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