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        <title>Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study</title>
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    <name type="personal">
        <namePart type="given">Yuchen</namePart>
        <namePart type="family">Zhang</namePart>
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    <name type="personal">
        <namePart type="given">Nianwen</namePart>
        <namePart type="family">Xue</namePart>
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            <title>Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)</title>
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        <name type="personal">
            <namePart type="given">Rada</namePart>
            <namePart type="family">Mihalcea</namePart>
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        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Shutova</namePart>
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        <name type="personal">
            <namePart type="given">Lun-Wei</namePart>
            <namePart type="family">Ku</namePart>
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        <name type="personal">
            <namePart type="given">Soujanya</namePart>
            <namePart type="family">Poria</namePart>
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    <abstract>Temporal Dependency Trees are a structured temporal representation that represents temporal relations among time expressions and events in a text as a dependency tree structure. Compared to traditional pair-wise temporal relation representations, temporal dependency trees facilitate efficient annotations, higher inter-annotator agreement, and efficient computations. However, annotations on temporal dependency trees so far have only been done by expert annotators, which is costly and time-consuming. In this paper, we introduce a method to crowdsource temporal dependency tree annotations, and show that this representation is intuitive and can be collected with high accuracy and agreement through crowdsourcing. We produce a corpus of temporal dependency trees, and present a baseline temporal dependency parser, trained and evaluated on this new corpus.</abstract>
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%0 Conference Proceedings
%T Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study
%A Zhang, Yuchen
%A Xue, Nianwen
%Y Mihalcea, Rada
%Y Shutova, Ekaterina
%Y Ku, Lun-Wei
%Y Evang, Kilian
%Y Poria, Soujanya
%S Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota
%F zhang-xue-2019-acquiring
%X Temporal Dependency Trees are a structured temporal representation that represents temporal relations among time expressions and events in a text as a dependency tree structure. Compared to traditional pair-wise temporal relation representations, temporal dependency trees facilitate efficient annotations, higher inter-annotator agreement, and efficient computations. However, annotations on temporal dependency trees so far have only been done by expert annotators, which is costly and time-consuming. In this paper, we introduce a method to crowdsource temporal dependency tree annotations, and show that this representation is intuitive and can be collected with high accuracy and agreement through crowdsourcing. We produce a corpus of temporal dependency trees, and present a baseline temporal dependency parser, trained and evaluated on this new corpus.
%R 10.18653/v1/S19-1019
%U https://aclanthology.org/S19-1019/
%U https://doi.org/10.18653/v1/S19-1019
%P 178-185

Markdown (Informal)

[Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study](https://aclanthology.org/S19-1019/) (Zhang & Xue, *SEM 2019)

• Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study (Zhang & Xue, *SEM 2019)

ACL

• Yuchen Zhang and Nianwen Xue. 2019. Acquiring Structured Temporal Representation via Crowdsourcing: A Feasibility Study. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 178–185, Minneapolis, Minnesota. Association for Computational Linguistics.