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        <title>Construction of CFSP Model Based on Non-Finetuning Large Language Model</title>
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        <namePart type="given">Huang</namePart>
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    <name type="personal">
        <namePart type="given">Cheng</namePart>
        <namePart type="family">Haibo</namePart>
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            <title>Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)</title>
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            <namePart type="given">Hongfei</namePart>
            <namePart type="family">Lin</namePart>
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            <namePart type="given">Hongye</namePart>
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            <namePart type="given">Bin</namePart>
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    <abstract>“Chinese Frame Semantic Parsing (CFSP) is an important task in the field of Chinese Natural Language Processing(NLP). Its goal is to extract the frame semantic structure from the sentence and realize the deep understanding of the events or situations involved in the sentence. This paper mainly studies the application of Large Language Model (LLM) for reasoning through Prompt Engineering without fine-tuning the model, and completes three subtasks of Chinese Framework Semantic Parsing tasks: frame identification, argument Identification and role identification. This paper proposes a Retrieval Augmented Generation (RAG) method for target words, and constructs more refined sample Few-Shot method. We achieved the second place on the B rankings in the open track in the “CCL2024-Eval The Second Chinese Frame Semantic Parsing”competition*.”</abstract>
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        <date>2024-07</date>
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%0 Conference Proceedings
%T Construction of CFSP Model Based on Non-Finetuning Large Language Model
%A Fugeng, Huang
%A Zhongbin, Guo
%A Wenting, Li
%A Haibo, Cheng
%Y Lin, Hongfei
%Y Tan, Hongye
%Y Li, Bin
%S Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
%D 2024
%8 July
%I Chinese Information Processing Society of China
%C Taiyuan, China
%G eng
%F fugeng-etal-2024-construction
%X “Chinese Frame Semantic Parsing (CFSP) is an important task in the field of Chinese Natural Language Processing(NLP). Its goal is to extract the frame semantic structure from the sentence and realize the deep understanding of the events or situations involved in the sentence. This paper mainly studies the application of Large Language Model (LLM) for reasoning through Prompt Engineering without fine-tuning the model, and completes three subtasks of Chinese Framework Semantic Parsing tasks: frame identification, argument Identification and role identification. This paper proposes a Retrieval Augmented Generation (RAG) method for target words, and constructs more refined sample Few-Shot method. We achieved the second place on the B rankings in the open track in the “CCL2024-Eval The Second Chinese Frame Semantic Parsing”competition*.”
%U https://aclanthology.org/2024.ccl-3.1/
%P 1-9

Markdown (Informal)

[Construction of CFSP Model Based on Non-Finetuning Large Language Model](https://aclanthology.org/2024.ccl-3.1/) (Fugeng et al., CCL 2024)

• Construction of CFSP Model Based on Non-Finetuning Large Language Model (Fugeng et al., CCL 2024)

ACL

• Huang Fugeng, Guo Zhongbin, Li Wenting, and Cheng Haibo. 2024. Construction of CFSP Model Based on Non-Finetuning Large Language Model. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations), pages 1–9, Taiyuan, China. Chinese Information Processing Society of China.