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Paper Abstract and Keywords
Presentation 2024-03-10 18:55
Language Model for Variable Definition Extraction from Chemical Process-related Papers
Shota Kato, Kotaro Nagayama, Manabu Kano (Kyoto Univ.) NLC2023-25
Abstract (in Japanese) (See Japanese page) 
(in English) Extracting variable definitions from scientific papers is crucial for understanding and leveraging research findings, yet the performance of current extraction methods can vary significantly across disciplines. This study addresses the challenge of variable extraction from documents related to chemical processes. We introduce an approach incorporating special tokens to signal the target variable for variable definition extraction. Our methodology, applied to the DeBERTaV3$_text{large}$ model, demonstrated a significant improvement over the current best-performing method, enhancing accuracy by 4.8 points to reach 86.9%. However, when implementing our approach with four BERT models, the results were only on par with the existing method. This discrepancy highlights the limitations of BERT-based models in capturing variable information effectively. Our findings underscore the importance of model selection in the domain-specific application of variable definition extraction.
Keyword (in Japanese) (See Japanese page) 
(in English) Variable definition extraction / DeBERTaV3 / BERT / Scholarly document processing / Domain-specific NLP / Chemical process / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 416, NLC2023-25, pp. 13-18, March 2024.
Paper # NLC2023-25 
Date of Issue 2024-03-03 (NLC) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF NLC2023-25

Conference Information
Committee NLC IPSJ-NL  
Conference Date 2024-03-10 - 2024-03-11 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Applications of natural language processing, and etc. 
Paper Information
Registration To NLC 
Conference Code 2024-03-NLC-NL 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Language Model for Variable Definition Extraction from Chemical Process-related Papers 
Sub Title (in English)  
Keyword(1) Variable definition extraction  
Keyword(2) DeBERTaV3  
Keyword(3) BERT  
Keyword(4) Scholarly document processing  
Keyword(5) Domain-specific NLP  
Keyword(6) Chemical process  
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Keyword(8)  
1st Author's Name Shota Kato  
1st Author's Affiliation Kyoto University (Kyoto Univ.)
2nd Author's Name Kotaro Nagayama  
2nd Author's Affiliation Kyoto University (Kyoto Univ.)
3rd Author's Name Manabu Kano  
3rd Author's Affiliation Kyoto University (Kyoto Univ.)
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Speaker Author-1 
Date Time 2024-03-10 18:55:00 
Presentation Time 25 minutes 
Registration for NLC 
Paper # NLC2023-25 
Volume (vol) vol.123 
Number (no) no.416 
Page pp.13-18 
#Pages 6 
Date of Issue 2024-03-03 (NLC) 

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