In communication, textual data are a vital attribute. In all languages, ambiguous or polysemous words' meaning changes depending on the context in which they are used. The ability to determine the ambiguous word's correct meaning is a Know-distill challenging task in natural language processing (NLP). Word sense disambiguation (WSD) is an NLP process to analyze and determine the correct meaning of polysemous words in a text. WSD is a computational linguistics task that automatically identifies the polysemous word's set of senses. Based on the context some word comes into view, WSD recognizes and tags the word to its correct priori known meaning. Semitic languages like Arabic have even more significant challenges than other languages since Arabic lacks diacritics, standardization, and a massive shortage of available resources. Recently, many approaches and techniques have been suggested to solve word ambiguity dilemmas in many different ways and several languages. In this review paper, an extensive survey of research works is presented, seeking to solve Arabic word sense disambiguation with the existing AWSD datasets.

中文翻译：

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自然语言处理应用中阿拉伯语词义消歧的综合评述

在通信中，文本数据是一个至关重要的属性。在所有语言中，模棱两可或多义词的含义会根据使用它们的上下文而变化。确定模棱两可词正确含义的能力是自然语言处理 (NLP) 中的一项 Know-distill 具有挑战性的任务。词义消歧 (WSD) 是一种 NLP 过程，用于分析和确定文本中多义词的正确含义。WSD 是一项计算语言学任务，可自动识别多义词的一组意义。根据上下文，某个单词进入视野，WSD 识别该单词并将其标记为正确的先验已知含义。像阿拉伯语这样的闪族语言比其他语言面临更大的挑战，因为阿拉伯语缺乏变音符号、标准化和可用资源的严重短缺。最近，已经提出了许多方法和技术来以多种不同的方式和多种语言解决单词歧义困境。在这篇评论论文中，对研究工作进行了广泛的调查，旨在解决与现有 AWSD 数据集的阿拉伯语词义消歧问题。