<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="zheng-etal-2024-comprehensive">
    <titleInfo>
        <title>A Comprehensive Survey on Document-Level Information Extraction</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Hanwen</namePart>
        <namePart type="family">Zheng</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Sijia</namePart>
        <namePart type="family">Wang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Lifu</namePart>
        <namePart type="family">Huang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2024-11</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Workshop on the Future of Event Detection (FuturED)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Joel</namePart>
            <namePart type="family">Tetreault</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Thien</namePart>
            <namePart type="given">Huu</namePart>
            <namePart type="family">Nguyen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Hemank</namePart>
            <namePart type="family">Lamba</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Amanda</namePart>
            <namePart type="family">Hughes</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Miami, Florida, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>enter abstract here</abstract>
    <identifier type="citekey">zheng-etal-2024-comprehensive</identifier>
    <location>
        <url>https://aclanthology.org/2024.futured-1.6</url>
    </location>
    <part>
        <date>2024-11</date>
        <extent unit="page">
            <start>58</start>
            <end>72</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T A Comprehensive Survey on Document-Level Information Extraction
%A Zheng, Hanwen
%A Wang, Sijia
%A Huang, Lifu
%Y Tetreault, Joel
%Y Nguyen, Thien Huu
%Y Lamba, Hemank
%Y Hughes, Amanda
%S Proceedings of the Workshop on the Future of Event Detection (FuturED)
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F zheng-etal-2024-comprehensive
%X enter abstract here
%U https://aclanthology.org/2024.futured-1.6
%P 58-72

Markdown (Informal)

[A Comprehensive Survey on Document-Level Information Extraction](https://aclanthology.org/2024.futured-1.6) (Zheng et al., FuturED 2024)

• A Comprehensive Survey on Document-Level Information Extraction (Zheng et al., FuturED 2024)

ACL

• Hanwen Zheng, Sijia Wang, and Lifu Huang. 2024. A Comprehensive Survey on Document-Level Information Extraction. In Proceedings of the Workshop on the Future of Event Detection (FuturED), pages 58–72, Miami, Florida, USA. Association for Computational Linguistics.