Evaluating Word Sense Disambiguation Techniques for Punjabi Language: A Comparative Analysis

Gursewak Singh
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Abstract

Word Sense Disambiguation (WSD) is a fundamental task in natural language processing (NLP) that focuses on determining the precise meaning of a word by analyzing its contextual usage.This paper presents a comprehensive analysis of various WSD techniques applied to the Punjabi language, including supervised, unsupervised, and knowledge-based methods. We compare the accuracy, performance, benefits, drawbacks, and resource requirements of these techniques.The study aims to provide a detailed overview of the state of WSD for Punjabi, with visual representations such as tables and graphs to illustrate comparative performance. Key Words: Word Sense Disambiguation, Punjabi Language, Natural Language Processing, Supervised Learning, Unsupervised Learning, Knowledge-Based Approach
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评估旁遮普语的词义消歧技术:比较分析
词义消歧(WSD)是自然语言处理(NLP)中的一项基本任务,其重点是通过分析单词的上下文用法来确定单词的准确含义。本文全面分析了应用于旁遮普语的各种 WSD 技术,包括有监督、无监督和基于知识的方法。我们对这些技术的准确性、性能、优点、缺点和资源要求进行了比较。本研究旨在提供旁遮普语 WSD 现状的详细概述,并通过表格和图表等可视化表现形式来说明比较性能。关键字词义消歧、旁遮普语、自然语言处理、监督学习、非监督学习、基于知识的方法
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