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  license: cc-by-nc-sa-4.0
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  license: cc-by-nc-sa-4.0
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+ # Dataset Card for environmental_claims
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+
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+ ## Dataset Description
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+
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+ - **Homepage:**
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+ - **Repository:**
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+ - **Paper:**
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+ - **Leaderboard:**
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+ - **Point of Contact:**
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+
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+ ### Dataset Summary
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+ We introduce an expert-annotated dataset for detecting real-world environmental claims made by listed companies.
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+
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+ ### Supported Tasks and Leaderboards
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+ The dataset supports a binary classification task of whether a given sentence is an environmental claim or not.
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+ ### Languages
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+ The text in the dataset is in English.
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+ ```
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+ {
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+ "text": "It will enable E.ON to acquire and leverage a comprehensive understanding of the transfor- mation of the energy system and the interplay between the individual submarkets in regional and local energy supply sys- tems.",
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+ "label": 0
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+ }
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+ ```
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+
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+ ### Data Fields
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+ - text: a sentence extracted from corporate annual reports, sustainability reports and earning calls transcripts
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+ - label: the label (0 -> no environmental claim, 1 -> environmental claim)
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+
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+ ### Data Splits
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+
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+ The dataset is split into:
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+ - train: 2,400
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+ - validation: 300
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+ - test: 300
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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+ [More Information Needed]
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+ Our dataset contains environmental claims by firms, often in the financial domain. We collect text from corporate annual reports, sustainability reports, and earning calls transcripts.
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+ For more information regarding our sample selection, please refer to Appendix B of our paper, which is provided for [citation](#Citation Information).
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+ #### Who are the source language producers?
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+ Mainly large listed companies.
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+ ### Annotations
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+ #### Annotation process
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+ For more information on our annotation process and annotation guidelines, please refer to Appendix C of our paper, which is provided for [citation](#Citation Information).
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+ #### Who are the annotators?
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+ The authors and students at University of Zurich with majors in finance and sustainable finance.
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+ ### Personal and Sensitive Information
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+ Since our text sources contain public information, no personal and sensitive information should be included.
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+ ## Considerations for Using the Data
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+ ### Social Impact of Dataset
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+ [More Information Needed]
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+ ### Discussion of Biases
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+ [More Information Needed]
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+ ### Other Known Limitations
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+ [More Information Needed]
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+
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+ ## Additional Information
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+ ### Dataset Curators
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+ - Dominik Stammbach
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+ - Nicolas Webersinke
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+ - Julia Anna Bingler
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+ - Mathias Kraus
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+ - Markus Leippold
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+
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+ ### Licensing Information
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+ This dataset is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license (cc-by-nc-sa-4.0). To view a copy of this license, visit [creativecommons.org/licenses/by-nc-sa/4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/).
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+ If you are interested in commercial use of the dataset, please contact the ClimateBert team at [[email protected]](mailto:[email protected]).
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+ ### Citation Information
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+ ```bibtex
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+ @misc{stammbach2022environmentalclaims,
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+ title = {A Dataset for Detecting Real-World Environmental Claims},
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+ author = {Stammbach, Dominik and Webersinke, Nicolas and Bingler, Julia Anna and Kraus, Mathias and Leippold, Markus},
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+ year = {2022},
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+ doi = {10.48550/ARXIV.2209.00507},
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+ url = {https://arxiv.org/abs/2209.00507},
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+ publisher = {arXiv},
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+ }
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+ ```
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+
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+ ### Contributions
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+
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+ Thanks to [@webersni](https://github.com/webersni) for adding this dataset.