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    <titleInfo>
        <title>A Corpus Study of Creating Rule-Based Enhanced Universal Dependencies for German</title>
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    <name type="personal">
        <namePart type="given">Teresa</namePart>
        <namePart type="family">Bürkle</namePart>
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    <name type="personal">
        <namePart type="given">Stefan</namePart>
        <namePart type="family">Grünewald</namePart>
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    <name type="personal">
        <namePart type="given">Annemarie</namePart>
        <namePart type="family">Friedrich</namePart>
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        <dateIssued>2021-11</dateIssued>
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            <title>Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop</title>
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        <name type="personal">
            <namePart type="given">Claire</namePart>
            <namePart type="family">Bonial</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Nianwen</namePart>
            <namePart type="family">Xue</namePart>
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    <abstract>In this paper, we present a first attempt at enriching German Universal Dependencies (UD) treebanks with enhanced dependencies. Similarly to the converter for English (Schuster and Manning, 2016), we develop a rule-based system for deriving enhanced dependencies from the basic layer, covering three linguistic phenomena: relative clauses, coordination, and raising/control. For quality control, we manually correct or validate a set of 196 sentences, finding that around 90% of added relations are correct. Our data analysis reveals that difficulties arise mainly due to inconsistencies in the basic layer annotations. We show that the English system is in general applicable to German data, but that adapting to the particularities of the German treebanks and language increases precision and recall by up to 10%. Comparing the application of our converter on gold standard dependencies vs. automatic parses, we find that F1 drops by around 10% in the latter setting due to error propagation. Finally, an enhanced UD parser trained on a converted treebank performs poorly when evaluated against our annotations, indicating that more work remains to be done to create gold standard enhanced German treebanks.</abstract>
    <identifier type="citekey">burkle-etal-2021-corpus</identifier>
    <identifier type="doi">10.18653/v1/2021.law-1.9</identifier>
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        <date>2021-11</date>
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%0 Conference Proceedings
%T A Corpus Study of Creating Rule-Based Enhanced Universal Dependencies for German
%A Bürkle, Teresa
%A Grünewald, Stefan
%A Friedrich, Annemarie
%Y Bonial, Claire
%Y Xue, Nianwen
%S Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop
%D 2021
%8 November
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F burkle-etal-2021-corpus
%X In this paper, we present a first attempt at enriching German Universal Dependencies (UD) treebanks with enhanced dependencies. Similarly to the converter for English (Schuster and Manning, 2016), we develop a rule-based system for deriving enhanced dependencies from the basic layer, covering three linguistic phenomena: relative clauses, coordination, and raising/control. For quality control, we manually correct or validate a set of 196 sentences, finding that around 90% of added relations are correct. Our data analysis reveals that difficulties arise mainly due to inconsistencies in the basic layer annotations. We show that the English system is in general applicable to German data, but that adapting to the particularities of the German treebanks and language increases precision and recall by up to 10%. Comparing the application of our converter on gold standard dependencies vs. automatic parses, we find that F1 drops by around 10% in the latter setting due to error propagation. Finally, an enhanced UD parser trained on a converted treebank performs poorly when evaluated against our annotations, indicating that more work remains to be done to create gold standard enhanced German treebanks.
%R 10.18653/v1/2021.law-1.9
%U https://aclanthology.org/2021.law-1.9
%U https://doi.org/10.18653/v1/2021.law-1.9
%P 85-95

Markdown (Informal)

[A Corpus Study of Creating Rule-Based Enhanced Universal Dependencies for German](https://aclanthology.org/2021.law-1.9) (Bürkle et al., LAW 2021)

• A Corpus Study of Creating Rule-Based Enhanced Universal Dependencies for German (Bürkle et al., LAW 2021)

ACL

• Teresa Bürkle, Stefan Grünewald, and Annemarie Friedrich. 2021. A Corpus Study of Creating Rule-Based Enhanced Universal Dependencies for German. In Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop, pages 85–95, Punta Cana, Dominican Republic. Association for Computational Linguistics.