<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="nederhof-2019-calculating">
    <titleInfo>
        <title>Calculating the Optimal Step in Shift-Reduce Dependency Parsing: From Cubic to Linear Time</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Mark-Jan</namePart>
        <namePart type="family">Nederhof</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <genre authority="bibutilsgt">journal article</genre>
    <relatedItem type="host">
        <titleInfo>
            <title>Transactions of the Association for Computational Linguistics</title>
        </titleInfo>
        <originInfo>
            <issuance>continuing</issuance>
            <publisher>MIT Press</publisher>
            <place>
                <placeTerm type="text">Cambridge, MA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">periodical</genre>
        <genre authority="bibutilsgt">academic journal</genre>
    </relatedItem>
    <abstract>We present a new cubic-time algorithm to calculate the optimal next step in shift-reduce dependency parsing, relative to ground truth, commonly referred to as dynamic oracle. Unlike existing algorithms, it is applicable if the training corpus contains non-projective structures. We then show that for a projective training corpus, the time complexity can be improved from cubic to linear.</abstract>
    <identifier type="citekey">nederhof-2019-calculating</identifier>
    <identifier type="doi">10.1162/tacl_a_00268</identifier>
    <location>
        <url>https://aclanthology.org/Q19-1018</url>
    </location>
    <part>
        <date>2019</date>
        <detail type="volume"><number>7</number></detail>
        <extent unit="page">
            <start>283</start>
            <end>296</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Journal Article
%T Calculating the Optimal Step in Shift-Reduce Dependency Parsing: From Cubic to Linear Time
%A Nederhof, Mark-Jan
%J Transactions of the Association for Computational Linguistics
%D 2019
%V 7
%I MIT Press
%C Cambridge, MA
%F nederhof-2019-calculating
%X We present a new cubic-time algorithm to calculate the optimal next step in shift-reduce dependency parsing, relative to ground truth, commonly referred to as dynamic oracle. Unlike existing algorithms, it is applicable if the training corpus contains non-projective structures. We then show that for a projective training corpus, the time complexity can be improved from cubic to linear.
%R 10.1162/tacl_a_00268
%U https://aclanthology.org/Q19-1018
%U https://doi.org/10.1162/tacl_a_00268
%P 283-296

Markdown (Informal)

[Calculating the Optimal Step in Shift-Reduce Dependency Parsing: From Cubic to Linear Time](https://aclanthology.org/Q19-1018) (Nederhof, TACL 2019)

• Calculating the Optimal Step in Shift-Reduce Dependency Parsing: From Cubic to Linear Time (Nederhof, TACL 2019)

ACL

• Mark-Jan Nederhof. 2019. Calculating the Optimal Step in Shift-Reduce Dependency Parsing: From Cubic to Linear Time. Transactions of the Association for Computational Linguistics, 7:283–296.