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Paper Abstract and Keywords
Presentation 2023-09-06 13:45
An Investigation of the Performance of Large-scale Generative Language Models on Subjective and Objective Emotion Estimation
Mizuki Tada, Makoto Okada, Naoki Mori (Osaka Metropolitan Univ.) NLC2023-2
Abstract (in Japanese) (See Japanese page) 
(in English) The cost of annotating datasets is often an issue in natural language processing tasks. One way to reduce costs is to use machine learning models for automatic annotation, and the availability of large-scale generative language models has attracted much attention in recent years. In this study, we conducted annotation using GPT-3.5, one of the large-scale generative language models, on WRIME, a dataset of subjective and objective sentiment analysis. Based on the experimental results, we confirmed the validity and trends of the annotations, and discussed the possibility of using generative large-scale language models for automatic annotation.
Keyword (in Japanese) (See Japanese page) 
(in English) Large Language Models / Automatic Annotation / Sentiment Analysis / WRIME Dataset / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 176, NLC2023-2, pp. 7-11, Sept. 2023.
Paper # NLC2023-2 
Date of Issue 2023-08-30 (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 NLC2023-2

Conference Information
Committee NLC  
Conference Date 2023-09-06 - 2023-09-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Osaka Metropolitan University. Nakamozu Campus. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The 20th Text Analytics Symposium 
Paper Information
Registration To NLC 
Conference Code 2023-09-NLC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Investigation of the Performance of Large-scale Generative Language Models on Subjective and Objective Emotion Estimation 
Sub Title (in English)  
Keyword(1) Large Language Models  
Keyword(2) Automatic Annotation  
Keyword(3) Sentiment Analysis  
Keyword(4) WRIME Dataset  
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1st Author's Name Mizuki Tada  
1st Author's Affiliation Osaka Metropolitan University (Osaka Metropolitan Univ.)
2nd Author's Name Makoto Okada  
2nd Author's Affiliation Osaka Metropolitan University (Osaka Metropolitan Univ.)
3rd Author's Name Naoki Mori  
3rd Author's Affiliation Osaka Metropolitan University (Osaka Metropolitan Univ.)
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Speaker Author-1 
Date Time 2023-09-06 13:45:00 
Presentation Time 25 minutes 
Registration for NLC 
Paper # NLC2023-2 
Volume (vol) vol.123 
Number (no) no.176 
Page pp.7-11 
#Pages 5 
Date of Issue 2023-08-30 (NLC) 

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