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        <title>discopy: A Neural System for Shallow Discourse Parsing</title>
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    <name type="personal">
        <namePart type="given">René</namePart>
        <namePart type="family">Knaebel</namePart>
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            <title>Proceedings of the 2nd Workshop on Computational Approaches to Discourse</title>
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            <namePart type="given">Chloé</namePart>
            <namePart type="family">Braud</namePart>
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        <name type="personal">
            <namePart type="given">Christian</namePart>
            <namePart type="family">Hardmeier</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Junyi</namePart>
            <namePart type="given">Jessy</namePart>
            <namePart type="family">Li</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Annie</namePart>
            <namePart type="family">Louis</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Michael</namePart>
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        <name type="personal">
            <namePart type="given">Amir</namePart>
            <namePart type="family">Zeldes</namePart>
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    <abstract>This paper demonstrates discopy, a novel framework that makes it easy to design components for end-to-end shallow discourse parsing. For the purpose of demonstration, we implement recent neural approaches and integrate contextualized word embeddings to predict explicit and non-explicit discourse relations. Our proposed neural feature-free system performs competitively to systems presented at the latest Shared Task on Shallow Discourse Parsing. Finally, a web front end is shown that simplifies the inspection of annotated documents. The source code, documentation, and pretrained models are publicly accessible.</abstract>
    <identifier type="citekey">knaebel-2021-discopy</identifier>
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%0 Conference Proceedings
%T discopy: A Neural System for Shallow Discourse Parsing
%A Knaebel, René
%Y Braud, Chloé
%Y Hardmeier, Christian
%Y Li, Junyi Jessy
%Y Louis, Annie
%Y Strube, Michael
%Y Zeldes, Amir
%S Proceedings of the 2nd Workshop on Computational Approaches to Discourse
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic and Online
%F knaebel-2021-discopy
%X This paper demonstrates discopy, a novel framework that makes it easy to design components for end-to-end shallow discourse parsing. For the purpose of demonstration, we implement recent neural approaches and integrate contextualized word embeddings to predict explicit and non-explicit discourse relations. Our proposed neural feature-free system performs competitively to systems presented at the latest Shared Task on Shallow Discourse Parsing. Finally, a web front end is shown that simplifies the inspection of annotated documents. The source code, documentation, and pretrained models are publicly accessible.
%R 10.18653/v1/2021.codi-main.12
%U https://aclanthology.org/2021.codi-main.12
%U https://doi.org/10.18653/v1/2021.codi-main.12
%P 128-133

Markdown (Informal)

[discopy: A Neural System for Shallow Discourse Parsing](https://aclanthology.org/2021.codi-main.12) (Knaebel, CODI 2021)

• discopy: A Neural System for Shallow Discourse Parsing (Knaebel, CODI 2021)

ACL

• René Knaebel. 2021. discopy: A Neural System for Shallow Discourse Parsing. In Proceedings of the 2nd Workshop on Computational Approaches to Discourse, pages 128–133, Punta Cana, Dominican Republic and Online. Association for Computational Linguistics.