Implementing Conditional Random Fields on English Text Grammar Analysis

Abstract

This study explores the implementaion of the Conditional Random Fields (CRF) algorithm in the grammatical analysis of English texts, specifically in the task of Part of Speech (POS) tagging. CRF is a statistical model effective in classifying words into grammatical categories such as nouns, verbs, adjectives, and others. The research methodology includes a literature review and experimental implementation using labeled datasets, integrated into a web-based application. The implementation results demonstrate that the CRF model provides accurate tagging results and can be utilized for sentence structure analysis in English texts. The application is developed using the Python programming language, supported by the NLTK and sklearn-crfsuite libraries, and uses the Flask framework for the user interface. This research is expected to contribute to the development of technology-based tools for English language learning.