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        <title>A Cognitive Approach to Annotating Causal Constructions in a Cross-Genre Corpus</title>
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    <name type="personal">
        <namePart type="given">Angela</namePart>
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            <namePart type="family">Pradhan</namePart>
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    <abstract>We present a scheme for annotating causal language in various genres of text. Our annotation scheme is built on the popular categories of cause, enable, and prevent. These vague categories have many edge cases in natural language, and as such can prove difficult for annotators to consistently identify in practice. We introduce a decision based annotation method for handling these edge cases. We demonstrate that, by utilizing this method, annotators are able to achieve inter-annotator agreement which is comparable to that of previous studies. Furthermore, our method performs equally well across genres, highlighting the robustness of our annotation scheme. Finally, we observe notable variation in usage and frequency of causal language across different genres.</abstract>
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        <url>https://aclanthology.org/2022.law-1.18</url>
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%0 Conference Proceedings
%T A Cognitive Approach to Annotating Causal Constructions in a Cross-Genre Corpus
%A Cao, Angela
%A Williamson, Gregor
%A Choi, Jinho D.
%Y Pradhan, Sameer
%Y Kuebler, Sandra
%S Proceedings of the 16th Linguistic Annotation Workshop (LAW-XVI) within LREC2022
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F cao-etal-2022-cognitive
%X We present a scheme for annotating causal language in various genres of text. Our annotation scheme is built on the popular categories of cause, enable, and prevent. These vague categories have many edge cases in natural language, and as such can prove difficult for annotators to consistently identify in practice. We introduce a decision based annotation method for handling these edge cases. We demonstrate that, by utilizing this method, annotators are able to achieve inter-annotator agreement which is comparable to that of previous studies. Furthermore, our method performs equally well across genres, highlighting the robustness of our annotation scheme. Finally, we observe notable variation in usage and frequency of causal language across different genres.
%U https://aclanthology.org/2022.law-1.18
%P 151-159

Markdown (Informal)

[A Cognitive Approach to Annotating Causal Constructions in a Cross-Genre Corpus](https://aclanthology.org/2022.law-1.18) (Cao et al., LAW 2022)

• A Cognitive Approach to Annotating Causal Constructions in a Cross-Genre Corpus (Cao et al., LAW 2022)

ACL

• Angela Cao, Gregor Williamson, and Jinho D. Choi. 2022. A Cognitive Approach to Annotating Causal Constructions in a Cross-Genre Corpus. In Proceedings of the 16th Linguistic Annotation Workshop (LAW-XVI) within LREC2022, pages 151–159, Marseille, France. European Language Resources Association.