<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="pannach-2023-orpheus">
    <titleInfo>
        <title>“Orpheus Came to His End by Being Struck by a Thunderbolt”: Annotating Events in Mythological Sequences</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Franziska</namePart>
        <namePart type="family">Pannach</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2023-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Jakob</namePart>
            <namePart type="family">Prange</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Annemarie</namePart>
            <namePart type="family">Friedrich</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Toronto, Canada</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>The mythological domain has various ways of expressing events and background knowledge. Using data extracted according to the hylistic approach (Zgoll, 2019), we annotated a data set of 6315 sentences from various mythological contexts and geographical origins, like Ancient Greece and Rome or Mesopotamia, into four categories: single-point events (e.g. actions), durative-constant (background knowledge, continuous states), durative-initial, and durative-resultativ. This data is used to train a classifier, which is able to reliably distinguish event types.</abstract>
    <identifier type="citekey">pannach-2023-orpheus</identifier>
    <identifier type="doi">10.18653/v1/2023.law-1.2</identifier>
    <location>
        <url>https://aclanthology.org/2023.law-1.2</url>
    </location>
    <part>
        <date>2023-07</date>
        <extent unit="page">
            <start>10</start>
            <end>18</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T “Orpheus Came to His End by Being Struck by a Thunderbolt”: Annotating Events in Mythological Sequences
%A Pannach, Franziska
%Y Prange, Jakob
%Y Friedrich, Annemarie
%S Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F pannach-2023-orpheus
%X The mythological domain has various ways of expressing events and background knowledge. Using data extracted according to the hylistic approach (Zgoll, 2019), we annotated a data set of 6315 sentences from various mythological contexts and geographical origins, like Ancient Greece and Rome or Mesopotamia, into four categories: single-point events (e.g. actions), durative-constant (background knowledge, continuous states), durative-initial, and durative-resultativ. This data is used to train a classifier, which is able to reliably distinguish event types.
%R 10.18653/v1/2023.law-1.2
%U https://aclanthology.org/2023.law-1.2
%U https://doi.org/10.18653/v1/2023.law-1.2
%P 10-18

Markdown (Informal)

[“Orpheus Came to His End by Being Struck by a Thunderbolt”: Annotating Events in Mythological Sequences](https://aclanthology.org/2023.law-1.2) (Pannach, LAW 2023)

• “Orpheus Came to His End by Being Struck by a Thunderbolt”: Annotating Events in Mythological Sequences (Pannach, LAW 2023)

ACL

• Franziska Pannach. 2023. “Orpheus Came to His End by Being Struck by a Thunderbolt”: Annotating Events in Mythological Sequences. In Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII), pages 10–18, Toronto, Canada. Association for Computational Linguistics.