<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="bikaun-etal-2022-quickgraph">
    <titleInfo>
        <title>QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Tyler</namePart>
        <namePart type="family">Bikaun</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Michael</namePart>
        <namePart type="family">Stewart</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Wei</namePart>
        <namePart type="family">Liu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2022-05</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Valerio</namePart>
            <namePart type="family">Basile</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Zornitsa</namePart>
            <namePart type="family">Kozareva</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sanja</namePart>
            <namePart type="family">Stajner</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Dublin, Ireland</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Acquiring high-quality annotated corpora for complex multi-task information extraction (MT-IE) is an arduous and costly process for human-annotators. Adoption of unsupervised techniques for automated annotation have thus become popular. However, these techniques rely heavily on dictionaries, gazetteers, and knowledge bases. While such resources are abundant for general domains, they are scarce for specialised technical domains. To tackle this challenge, we present QuickGraph, the first collaborative MT-IE annotation tool built with indirect weak supervision and clustering to maximise annotator productivity. QuickGraph’s main contribution is a set of novel features that enable knowledge graph extraction through rapid and consistent complex multi-task entity and relation annotation. In this paper, we discuss these key features and qualitatively compare QuickGraph to existing annotation tools.</abstract>
    <identifier type="citekey">bikaun-etal-2022-quickgraph</identifier>
    <identifier type="doi">10.18653/v1/2022.acl-demo.27</identifier>
    <location>
        <url>https://aclanthology.org/2022.acl-demo.27</url>
    </location>
    <part>
        <date>2022-05</date>
        <extent unit="page">
            <start>270</start>
            <end>278</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text
%A Bikaun, Tyler
%A Stewart, Michael
%A Liu, Wei
%Y Basile, Valerio
%Y Kozareva, Zornitsa
%Y Stajner, Sanja
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F bikaun-etal-2022-quickgraph
%X Acquiring high-quality annotated corpora for complex multi-task information extraction (MT-IE) is an arduous and costly process for human-annotators. Adoption of unsupervised techniques for automated annotation have thus become popular. However, these techniques rely heavily on dictionaries, gazetteers, and knowledge bases. While such resources are abundant for general domains, they are scarce for specialised technical domains. To tackle this challenge, we present QuickGraph, the first collaborative MT-IE annotation tool built with indirect weak supervision and clustering to maximise annotator productivity. QuickGraph’s main contribution is a set of novel features that enable knowledge graph extraction through rapid and consistent complex multi-task entity and relation annotation. In this paper, we discuss these key features and qualitatively compare QuickGraph to existing annotation tools.
%R 10.18653/v1/2022.acl-demo.27
%U https://aclanthology.org/2022.acl-demo.27
%U https://doi.org/10.18653/v1/2022.acl-demo.27
%P 270-278

Markdown (Informal)

[QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text](https://aclanthology.org/2022.acl-demo.27) (Bikaun et al., ACL 2022)

• QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text (Bikaun et al., ACL 2022)

ACL

• Tyler Bikaun, Michael Stewart, and Wei Liu. 2022. QuickGraph: A Rapid Annotation Tool for Knowledge Graph Extraction from Technical Text. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pages 270–278, Dublin, Ireland. Association for Computational Linguistics.