Some Means of Processing Electronic Text Documents

Oleksandr O. Letychevskyi, M. Morokhovets, N. M. Shchogoleva
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引用次数: 1

Abstract

Introduction. Digitization of legislation is an important area today, which is identified by the government as a priority. Creating digital legal documents and verifying them for compliance with the law is a necessary task in all areas of jurisprudence. This sets the task of automatic formalizing a legal document created as an arbitrary text in natural language. Purpose. Preparing a document for storage in digital format for further processing may require prior work with an original text. When using automatic means of linguistic analysis of the texts submitted in natural language, in particular, legal, which processes the text in sentences (working up the text sequentially sentence by sentence), problems of local and global nature arise. The problem of local nature is created, in particular, by the presence in the text of the sentences, which due to their considerable length are difficult to process (with the help of one or another tool of text analysis). The problem of a global nature arises when the semantic connection between the components of different sentences should be taken into account during the automatic processing of the text. The purpose of this work is to develop means for overcoming these problems. Results. A model for structuring long sentences containing enumerations as well as a method for eliminating the synonymy of object names referred to in the text, which is intended for automatic analysis, has been developed. Conclusion. Marking up sentences containing enumerations is useful, especially when the text is intended for analysis using a procedure that processes the text sentence by sentence. Structuring a sentence with an enumeration enables, on the one hand, to prepare the sentence for processing in parts, and on the other hand, not to lose the integrity of the sentence when processing in parts. In the method of eliminating the synonymy of names proposed in this paper, both the step of identifying the names of objects and the step of revealing the identity of names requires semantic analysis. To control the correctness of these steps, Oracle was introduced to improve the reliability of the result.
处理电子文本文档的几种方法
介绍立法数字化是当今的一个重要领域,政府将其确定为优先事项。创建数字法律文件并核实其是否符合法律规定是法学所有领域的一项必要任务。这设置了将创建为自然语言任意文本的法律文件自动形式化的任务。意图准备以数字格式存储的文档以供进一步处理可能需要事先处理原始文本。当对以自然语言,特别是法律语言提交的文本使用自动语言分析方法时,会出现局部和全局性的问题,该方法将文本按句子处理(逐句按顺序处理文本)。地方性质的问题是由句子在文本中的存在造成的,由于句子的长度相当长,很难处理(借助一种或另一种文本分析工具)。当在文本的自动处理过程中应该考虑不同句子组成部分之间的语义连接时,就会出现全局性的问题。这项工作的目的是开发克服这些问题的方法。后果已经开发了一种用于构造包含枚举的长句的模型,以及一种用于消除文本中提及的对象名称的同义词的方法,该方法旨在进行自动分析。结论标记包含枚举的句子是有用的,尤其是当文本用于使用逐句处理文本的程序进行分析时。用列举结构句子,一方面可以使句子为部分处理做好准备,另一方面,在部分处理时不会失去句子的完整性。在本文提出的消除名称同义的方法中,识别对象名称的步骤和揭示名称同一性的步骤都需要进行语义分析。为了控制这些步骤的正确性,引入了Oracle来提高结果的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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16
审稿时长
24 weeks
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