├── LICENSE ├── README.md ├── part1_evidence_synthesis.ipynb └── part2_paris_prompts.ipynb /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2024 climatechange-ai-tutorials 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # NLP Models for Climate Policy Analysis 2 | Explore how Natural Language Processing (NLP) can be used to assist in identifying and mapping climate-relevant literature using a supervised learning approach and leverage a state of the art Large Language Model (LLM) to classify climate policy documents. 3 | 4 | Author(s): 5 | * Daniel Spokoyny, Carnegie Mellon University, dspokoyn@cs.cmu.edu 6 | * Max Callaghan, Mercator Research Institute on Global Commons and Climate - Berlin, callaghan@mcc-berlin.net 7 | * Tobias Schimanski, University of Zurich, tobias.schimanski@df.uzh.ch 8 | 9 | Originally presented at Climate Change AI Summer School 2022 10 | 11 | ## Access this tutorial 12 | 13 | We recommend executing this notebook in a Colab environment to gain access to GPUs and to manage all necessary dependencies. 14 | 15 | Part 1: 16 | Open In Colab 17 | 18 | 19 | Part 2: 20 | Open In Colab 21 | 22 | 23 | Estimated time to execute end-to-end: 15 minutes 24 | 25 | ## Contribute to this tutorial 26 | 27 | Please refer to these [GitHub instructions](https://docs.github.com/en/get-started/exploring-projects-on-github/contributing-to-a-project#about-forking) to open a pull request via the "fork and pull request" workflow. 28 | 29 | Pull requests will be reviewed by members of the Climate Change AI Tutorials team for relevance, accuracy, and conciseness. 30 | 31 | ## Climate Change AI Tutorials 32 | Check out the [tutorials page](https://www.climatechange.ai/tutorials?) on our website for a full list of tutorials demonstrating how AI can be used to tackle problems related to climate change. 33 | 34 | ## License 35 | Usage of this tutorial is subject to the MIT License. 36 | 37 | ## Cite 38 | 39 | ### Plain Text 40 | Spokoyny, D., Callaghan, M, & Schimanski, T. (2024). NLP Models for Climate Policy Analysis [Tutorial]. In Climate Change AI Summer School. Climate Change AI. https://doi.org/10.5281/zenodo.12533572 41 | 42 | ### BibTeX 43 | 44 | ``` 45 | @misc{spokoyny2024nlp, 46 | title={NLP Models for Climate Policy Analysis}, 47 | author={Spokoyny, Daniel and Callaghan, Max and Schimanski, Tobias}, 48 | year={2024}, 49 | organization={Climate Change AI}, 50 | type={Tutorial}, 51 | doi={https://doi.org/10.5281/zenodo.12533572}, 52 | booktitle={Climate Change AI Summer School}, 53 | howpublished={\url{https://github.com/climatechange-ai-tutorials/nlp-policy-analysis}} 54 | } 55 | ``` 56 | --------------------------------------------------------------------------------