@inproceedings{alhamzeh-etal-2022-time,
title = "It{'}s Time to Reason: Annotating Argumentation Structures in Financial Earnings Calls: The {F}in{A}rg Dataset",
author = {Alhamzeh, Alaa and
Fonck, Romain and
Versm{\'e}e, Erwan and
Egyed-Zsigmond, El{\"o}d and
Kosch, Harald and
Brunie, Lionel},
editor = "Chen, Chung-Chi and
Huang, Hen-Hsen and
Takamura, Hiroya and
Chen, Hsin-Hsi",
booktitle = "Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.finnlp-1.22",
doi = "10.18653/v1/2022.finnlp-1.22",
pages = "163--169",
abstract = "With the goal of reasoning on the financial textual data, we present in this paper, a novel approach for annotating arguments, their components and relations in the transcripts of earnings conference calls (ECCs). The proposed scheme is driven from the argumentation theory at the micro-structure level of discourse. We further conduct a manual annotation study with four annotators on 136 documents. We obtained inter-annotator agreement of $lpha_{U}$ = 0.70 for argument components and $lpha$ = 0.81 for argument relations. The final created corpus, with the size of 804 documents, as well as the annotation guidelines are publicly available for researchers in the domains of computational argumentation, finance and FinNLP.",
}
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%0 Conference Proceedings
%T It’s Time to Reason: Annotating Argumentation Structures in Financial Earnings Calls: The FinArg Dataset
%A Alhamzeh, Alaa
%A Fonck, Romain
%A Versmée, Erwan
%A Egyed-Zsigmond, Elöd
%A Kosch, Harald
%A Brunie, Lionel
%Y Chen, Chung-Chi
%Y Huang, Hen-Hsen
%Y Takamura, Hiroya
%Y Chen, Hsin-Hsi
%S Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F alhamzeh-etal-2022-time
%X With the goal of reasoning on the financial textual data, we present in this paper, a novel approach for annotating arguments, their components and relations in the transcripts of earnings conference calls (ECCs). The proposed scheme is driven from the argumentation theory at the micro-structure level of discourse. We further conduct a manual annotation study with four annotators on 136 documents. We obtained inter-annotator agreement of lpha_U = 0.70 for argument components and lpha = 0.81 for argument relations. The final created corpus, with the size of 804 documents, as well as the annotation guidelines are publicly available for researchers in the domains of computational argumentation, finance and FinNLP.
%R 10.18653/v1/2022.finnlp-1.22
%U https://aclanthology.org/2022.finnlp-1.22
%U https://doi.org/10.18653/v1/2022.finnlp-1.22
%P 163-169
Markdown (Informal)
[It’s Time to Reason: Annotating Argumentation Structures in Financial Earnings Calls: The FinArg Dataset](https://aclanthology.org/2022.finnlp-1.22) (Alhamzeh et al., FinNLP 2022)
ACL