@inproceedings{li-etal-2023-word,
title = "Word-level Prefix/Suffix Sense Detection: A Case Study on Negation Sense with Few-shot Learning",
author = "Li, Yameng and
Li, Zicheng and
Chen, Ying and
Li, Shoushan",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-acl.484",
doi = "10.18653/v1/2023.findings-acl.484",
pages = "7651--7658",
abstract = "Morphological analysis is an important research issue in the field of natural language processing. In this study, we propose a context-free morphological analysis task, namely word-level prefix/suffix sense detection, which deals with the ambiguity of sense expressed by prefix/suffix. To research this novel task, we first annotate a corpus with prefixes/suffixes expressing negation (e.g., il-, un-, -less) and then propose a novel few-shot learning approach that applies an input-augmentation prompt to a token-replaced detection pre-training model. Empirical studies demonstrate the effectiveness of the proposed approach to word-level prefix/suffix negation sense detection.",
}
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<abstract>Morphological analysis is an important research issue in the field of natural language processing. In this study, we propose a context-free morphological analysis task, namely word-level prefix/suffix sense detection, which deals with the ambiguity of sense expressed by prefix/suffix. To research this novel task, we first annotate a corpus with prefixes/suffixes expressing negation (e.g., il-, un-, -less) and then propose a novel few-shot learning approach that applies an input-augmentation prompt to a token-replaced detection pre-training model. Empirical studies demonstrate the effectiveness of the proposed approach to word-level prefix/suffix negation sense detection.</abstract>
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%0 Conference Proceedings
%T Word-level Prefix/Suffix Sense Detection: A Case Study on Negation Sense with Few-shot Learning
%A Li, Yameng
%A Li, Zicheng
%A Chen, Ying
%A Li, Shoushan
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Findings of the Association for Computational Linguistics: ACL 2023
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F li-etal-2023-word
%X Morphological analysis is an important research issue in the field of natural language processing. In this study, we propose a context-free morphological analysis task, namely word-level prefix/suffix sense detection, which deals with the ambiguity of sense expressed by prefix/suffix. To research this novel task, we first annotate a corpus with prefixes/suffixes expressing negation (e.g., il-, un-, -less) and then propose a novel few-shot learning approach that applies an input-augmentation prompt to a token-replaced detection pre-training model. Empirical studies demonstrate the effectiveness of the proposed approach to word-level prefix/suffix negation sense detection.
%R 10.18653/v1/2023.findings-acl.484
%U https://aclanthology.org/2023.findings-acl.484
%U https://doi.org/10.18653/v1/2023.findings-acl.484
%P 7651-7658
Markdown (Informal)
[Word-level Prefix/Suffix Sense Detection: A Case Study on Negation Sense with Few-shot Learning](https://aclanthology.org/2023.findings-acl.484) (Li et al., Findings 2023)
ACL