# Evaluating ChatGPT as a Question Answering System: A Comprehensive Analysis and Comparison with Existing Models

Source: [Evaluating ChatGPT as a Question Answering System: A Comprehensive Analysis and Comparison with Existing Models](<https://www.sota2.com/research/paper/68fa717d1e209131cea519d5>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T02:07:38.985Z

Authors: Hossein Bahak, Farzaneh Taheri, Zahra Zojaji, Arefeh Kazemi

Published: 2023-12-11T08:49:18.000Z

## Abstract

In the current era, a multitude of language models has emerged to cater to user inquiries. Notably, the GPT-3.5 Turbo language model has gained substantial attention as the underlying technology for ChatGPT. Leveraging extensive parameters, this model adeptly responds to a wide range of questions. However, due to its reliance on internal knowledge, the accuracy of responses may not be absolute. This article scrutinizes ChatGPT as a Question Answering System (QAS), comparing its performance to other existing QASs. The primary focus is on evaluating ChatGPT's proficiency in extracting responses from provided paragraphs, a core QAS capability. Additionally, performance comparisons are made in scenarios without a surrounding passage. Multiple experiments, exploring response hallucination and considering question complexity, were conducted on ChatGPT. Evaluation employed well-known Question Answering (QA) datasets, including SQuAD, NewsQA, and PersianQuAD, across English and Persian languages. Metrics such as F-score, exact match, and accuracy were employed in the assessment. The study reveals that, while ChatGPT demonstrates competence as a generative model, it is less effective in question answering compared to task-specific models. Providing context improves its performance, and prompt engineering enhances precision, particularly for questions lacking explicit answers in provided paragraphs. ChatGPT excels at simpler factual questions compared to "how" and "why" question types. The evaluation highlights occurrences of hallucinations, where ChatGPT provides responses to questions without available answers in the provided context.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2312.07592>)

[PDF](<https://arxiv.org/pdf/2312.07592.pdf>)