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| pretty_name: SciFact | |
| license: cc-by-nc-2.0 | |
| task_categories: | |
| - text-classification | |
| language: | |
| - en | |
| ## Dataset Description | |
| This is yet another attempt to have a useful dataset script for SciFact. In constrast to the [original script by AllenAI](https://huggingface.co/datasets/allenai/scifact), we provide two views (config names), each **consisting of all the data**: | |
| 1. `as_claims`: Instances are claims with its `cited_doc_ids` resolved to their actual document content, saved in `cited_docs`, and | |
| 2. `as_documents`: Instances are documents with its related claims, i.e. claims that originally linked the document at hand via `cited_doc_ids`. | |
| ### Citation Information | |
| ``` | |
| @inproceedings{wadden-etal-2020-fact, | |
| title = "Fact or Fiction: Verifying Scientific Claims", | |
| author = "Wadden, David and | |
| Lin, Shanchuan and | |
| Lo, Kyle and | |
| Wang, Lucy Lu and | |
| van Zuylen, Madeleine and | |
| Cohan, Arman and | |
| Hajishirzi, Hannaneh", | |
| booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)", | |
| month = nov, | |
| year = "2020", | |
| address = "Online", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/2020.emnlp-main.609", | |
| doi = "10.18653/v1/2020.emnlp-main.609", | |
| pages = "7534--7550", | |
| } | |
| ``` |