<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="freitag-etal-2017-discourse">
    <titleInfo>
        <title>Discourse-Wide Extraction of Assay Frames from the Biological Literature</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Dayne</namePart>
        <namePart type="family">Freitag</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Paul</namePart>
        <namePart type="family">Kalmar</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Eric</namePart>
        <namePart type="family">Yeh</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2017-09</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Biomedical NLP Workshop associated with RANLP 2017</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Svetla</namePart>
            <namePart type="family">Boytcheva</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Kevin</namePart>
            <namePart type="given">Bretonnel</namePart>
            <namePart type="family">Cohen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Guergana</namePart>
            <namePart type="family">Savova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>INCOMA Ltd.</publisher>
            <place>
                <placeTerm type="text">Varna, Bulgaria</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>We consider the problem of populating multi-part knowledge frames from textual information distributed over multiple sentences in a document. We present a corpus constructed by aligning papers from the cellular signaling literature to a collection of approximately 50,000 reference frames curated by hand as part of a decade-long project. We present and evaluate two approaches to the challenging problem of reconstructing these frames, which formalize biological assays described in the literature. One approach is based on classifying candidate records nominated by sentence-local entity co-occurrence. In the second approach, we introduce a novel virtual register machine traverses an article and generates frames, trained on our reference data. Our evaluations show that success in the task ultimately hinges on an integration of evidence spread across the discourse.</abstract>
    <identifier type="citekey">freitag-etal-2017-discourse</identifier>
    <identifier type="doi">10.26615/978-954-452-044-1_003</identifier>
    <part>
        <date>2017-09</date>
        <extent unit="page">
            <start>15</start>
            <end>23</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Discourse-Wide Extraction of Assay Frames from the Biological Literature
%A Freitag, Dayne
%A Kalmar, Paul
%A Yeh, Eric
%Y Boytcheva, Svetla
%Y Cohen, Kevin Bretonnel
%Y Savova, Guergana
%Y Angelova, Galia
%S Proceedings of the Biomedical NLP Workshop associated with RANLP 2017
%D 2017
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F freitag-etal-2017-discourse
%X We consider the problem of populating multi-part knowledge frames from textual information distributed over multiple sentences in a document. We present a corpus constructed by aligning papers from the cellular signaling literature to a collection of approximately 50,000 reference frames curated by hand as part of a decade-long project. We present and evaluate two approaches to the challenging problem of reconstructing these frames, which formalize biological assays described in the literature. One approach is based on classifying candidate records nominated by sentence-local entity co-occurrence. In the second approach, we introduce a novel virtual register machine traverses an article and generates frames, trained on our reference data. Our evaluations show that success in the task ultimately hinges on an integration of evidence spread across the discourse.
%R 10.26615/978-954-452-044-1_003
%U https://doi.org/10.26615/978-954-452-044-1_003
%P 15-23

Markdown (Informal)

[Discourse-Wide Extraction of Assay Frames from the Biological Literature](https://doi.org/10.26615/978-954-452-044-1_003) (Freitag et al., RANLP 2017)

• Discourse-Wide Extraction of Assay Frames from the Biological Literature (Freitag et al., RANLP 2017)

ACL

• Dayne Freitag, Paul Kalmar, and Eric Yeh. 2017. Discourse-Wide Extraction of Assay Frames from the Biological Literature. In Proceedings of the Biomedical NLP Workshop associated with RANLP 2017, pages 15–23, Varna, Bulgaria. INCOMA Ltd..