<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="yahui-etal-2024-leveraging">
    <titleInfo>
        <title>Leveraging LLMs for Chinese Frame Semantic Parsing</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Liu</namePart>
        <namePart type="family">Yahui</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Gong</namePart>
        <namePart type="family">Chen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Zhang</namePart>
        <namePart type="family">Min</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <language>
        <languageTerm type="text">eng</languageTerm>
    </language>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Hongfei</namePart>
            <namePart type="family">Lin</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Hongye</namePart>
            <namePart type="family">Tan</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Bin</namePart>
            <namePart type="family">Li</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Chinese Information Processing Society of China</publisher>
            <place>
                <placeTerm type="text">Taiyuan, China</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>“We participate in the open track of the Chinese frame semantic parsing (CFSP) task, i.e., CCL24Eval Task 1, and our submission ranks first. FSP is an important task in Natural Language Processing, aiming to extract the frame semantic structures from sentences, which can be divided into three subtasks, e.g., Frame Identification (FI), Argument Identification (AI), and Role Identification (RI). In this paper, we use the LLM Gemini 1.0 to evaluate the three subtasks of CFSP, and present the techniques and strategies we employed to enhance subtasks performance. For FI, we leverage mapping and similarity strategies to minimize the candidate frames for each target word, which can reduce the complexity of the LLM in identifying the appropriate frame. For AI and RI subtasks, we utilize the results from small models as auxiliary information and apply data augmentation, self-training, and model ensemble techniques on these small models to further enhance the performance of subtasks.”</abstract>
    <identifier type="citekey">yahui-etal-2024-leveraging</identifier>
    <location>
        <url>https://aclanthology.org/2024.ccl-3.3/</url>
    </location>
    <part>
        <date>2024-07</date>
        <extent unit="page">
            <start>21</start>
            <end>31</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Leveraging LLMs for Chinese Frame Semantic Parsing
%A Yahui, Liu
%A Chen, Gong
%A Min, Zhang
%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 yahui-etal-2024-leveraging
%X “We participate in the open track of the Chinese frame semantic parsing (CFSP) task, i.e., CCL24Eval Task 1, and our submission ranks first. FSP is an important task in Natural Language Processing, aiming to extract the frame semantic structures from sentences, which can be divided into three subtasks, e.g., Frame Identification (FI), Argument Identification (AI), and Role Identification (RI). In this paper, we use the LLM Gemini 1.0 to evaluate the three subtasks of CFSP, and present the techniques and strategies we employed to enhance subtasks performance. For FI, we leverage mapping and similarity strategies to minimize the candidate frames for each target word, which can reduce the complexity of the LLM in identifying the appropriate frame. For AI and RI subtasks, we utilize the results from small models as auxiliary information and apply data augmentation, self-training, and model ensemble techniques on these small models to further enhance the performance of subtasks.”
%U https://aclanthology.org/2024.ccl-3.3/
%P 21-31

Markdown (Informal)

[Leveraging LLMs for Chinese Frame Semantic Parsing](https://aclanthology.org/2024.ccl-3.3/) (Yahui et al., CCL 2024)

• Leveraging LLMs for Chinese Frame Semantic Parsing (Yahui et al., CCL 2024)

ACL

• Liu Yahui, Gong Chen, and Zhang Min. 2024. Leveraging LLMs for Chinese Frame Semantic Parsing. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations), pages 21–31, Taiyuan, China. Chinese Information Processing Society of China.