<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="ogorman-etal-2018-amr">
    <titleInfo>
        <title>AMR Beyond the Sentence: the Multi-sentence AMR corpus</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Tim</namePart>
        <namePart type="family">O’Gorman</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Michael</namePart>
        <namePart type="family">Regan</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kira</namePart>
        <namePart type="family">Griffitt</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ulf</namePart>
        <namePart type="family">Hermjakob</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kevin</namePart>
        <namePart type="family">Knight</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Martha</namePart>
        <namePart type="family">Palmer</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2018-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 27th International Conference on Computational Linguistics</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Emily</namePart>
            <namePart type="given">M</namePart>
            <namePart type="family">Bender</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Leon</namePart>
            <namePart type="family">Derczynski</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Pierre</namePart>
            <namePart type="family">Isabelle</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Santa Fe, New Mexico, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>There are few corpora that endeavor to represent the semantic content of entire documents. We present a corpus that accomplishes one way of capturing document level semantics, by annotating coreference and similar phenomena (bridging and implicit roles) on top of gold Abstract Meaning Representations of sentence-level semantics. We present a new corpus of this annotation, with analysis of its quality, alongside a plausible baseline for comparison. It is hoped that this Multi-Sentence AMR corpus (MS-AMR) may become a feasible method for developing rich representations of document meaning, useful for tasks such as information extraction and question answering.</abstract>
    <identifier type="citekey">ogorman-etal-2018-amr</identifier>
    <location>
        <url>https://aclanthology.org/C18-1313</url>
    </location>
    <part>
        <date>2018-08</date>
        <extent unit="page">
            <start>3693</start>
            <end>3702</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T AMR Beyond the Sentence: the Multi-sentence AMR corpus
%A O’Gorman, Tim
%A Regan, Michael
%A Griffitt, Kira
%A Hermjakob, Ulf
%A Knight, Kevin
%A Palmer, Martha
%Y Bender, Emily M.
%Y Derczynski, Leon
%Y Isabelle, Pierre
%S Proceedings of the 27th International Conference on Computational Linguistics
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F ogorman-etal-2018-amr
%X There are few corpora that endeavor to represent the semantic content of entire documents. We present a corpus that accomplishes one way of capturing document level semantics, by annotating coreference and similar phenomena (bridging and implicit roles) on top of gold Abstract Meaning Representations of sentence-level semantics. We present a new corpus of this annotation, with analysis of its quality, alongside a plausible baseline for comparison. It is hoped that this Multi-Sentence AMR corpus (MS-AMR) may become a feasible method for developing rich representations of document meaning, useful for tasks such as information extraction and question answering.
%U https://aclanthology.org/C18-1313
%P 3693-3702

Markdown (Informal)

[AMR Beyond the Sentence: the Multi-sentence AMR corpus](https://aclanthology.org/C18-1313) (O’Gorman et al., COLING 2018)

• AMR Beyond the Sentence: the Multi-sentence AMR corpus (O’Gorman et al., COLING 2018)

ACL

• Tim O’Gorman, Michael Regan, Kira Griffitt, Ulf Hermjakob, Kevin Knight, and Martha Palmer. 2018. AMR Beyond the Sentence: the Multi-sentence AMR corpus. In Proceedings of the 27th International Conference on Computational Linguistics, pages 3693–3702, Santa Fe, New Mexico, USA. Association for Computational Linguistics.