Evaluating Chatbot Assistance in Historical Document Analysis

The article explores the potential of PDFGear Copilot, a chatbot-based PDF editing tool, in assisting with the analysis of historical documents. We evaluated the chatbot's performance on a document relating to the Slovenian War of Independence. We included 25 factual and 5 interpretative questions to address its formal characteristics and content details, assess its capacity for in-depth interpretation and contextualized critical analysis, and evaluate the chatbot’s language use and robustness. The chatbot exhibited some ability to answer factual questions, even though its performance varied. It demonstrated proficiency in navigating document structure, named entity recognition, and extracting basic document information. However, performance declined significantly in tasks such as document type identification, content details, and tasks requiring deeper text analysis. For interpretative questions, the chatbot's performance was notably inadequate, failing to link cause-and-effect relationships and provide the depth and nuance required for historical inquiries.

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Publication Details

Journal
Moderna arhivistika
Published
2024-12-10
DOI
https://doi.org/10.54356/ma/2024/biub3010
Citations
1
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.35
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article

Evaluating Chatbot Assistance in Historical Document Analysis

David Hazemali, Janez Osojnik, Tomaž Onič
1 citations
Moderna arhivistika
AI in Service Interactions
0.35
article

Evaluating Chatbot Assistance in Historical Document Analysis

David Hazemali, Janez Osojnik, Tomaž Onič
article en
1 citations

Abstract

The article explores the potential of PDFGear Copilot, a chatbot-based PDF editing tool, in assisting with the analysis of historical documents. We evaluated the chatbot's performance on a document relating to the Slovenian War of Independence. We included 25 factual and 5 interpretative questions to address its formal characteristics and content details, assess its capacity for in-depth interpretation and contextualized critical analysis, and evaluate the chatbot’s language use and robustness. The chatbot exhibited some ability to answer factual questions, even though its performance varied. It demonstrated proficiency in navigating document structure, named entity recognition, and extracting basic document information. However, performance declined significantly in tasks such as document type identification, content details, and tasks requiring deeper text analysis. For interpretative questions, the chatbot's performance was notably inadequate, failing to link cause-and-effect relationships and provide the depth and nuance required for historical inquiries.

Moderna arhivistikaVol. 2024 (7)(2)
University of Maribor (SI)
Quality Education
Openalex Percentile: Top 31%
AI in Service Interactions
0.35
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