Exploring Sentence Parsing: OpenAI API-Based and Hybrid Parser-Based Approaches

Abstract

This study focuses on the fundamental process of parsing sentences to create semantic graphs from textual documents. It introduces novel techniques for parsing phrases within semantic graph-based induction, employing both ChatGPT-based and Hybrid parser-based approaches. Through a thorough analysis, the study evaluates the performance of these methods in generating semantic networks from text, particularly in capturing detailed event descriptions and relationships. Results indicate a slight advantage in accuracy for the Hybrid parser-based approach (87%) compared to ChatGPT (85%) in sentence parsing tasks. Furthermore, efficiency analysis reveals that ChatGPT's response quality varies with prompt sizes, while the Hybrid parser-based method consistently maintains excellent response quality.