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--- |
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license: cc-by-nc-sa-4.0 |
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annotations_creators: |
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- expert-generated |
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language_creators: |
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- found |
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language: |
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- en |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 1K<n<10K |
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source_datasets: |
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- original |
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task_categories: |
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- text-classification |
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task_ids: |
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- text-classification |
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pretty_name: EnvironmentalClaims |
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--- |
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# Dataset Card for environmental_claims |
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## Dataset Description |
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- **Homepage:** [climatebert.ai](https://climatebert.ai) |
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- **Repository:** |
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- **Paper:** [arxiv.org/abs/2209.00507](https://arxiv.org/abs/2209.00507) |
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- **Leaderboard:** |
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- **Point of Contact:** [Dominik Stammbach](mailto:dominsta@ethz.ch) |
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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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### 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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## Dataset Structure |
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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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### 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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### Data Splits |
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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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## Dataset Creation |
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### Curation Rationale |
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[More Information Needed] |
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### Source Data |
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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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## 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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### 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 [hello@climatebert.ai](mailto:hello@climatebert.ai). |
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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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### Contributions |
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Thanks to [@webersni](https://github.com/webersni) for adding this dataset. |
