--- license: apache-2.0 tags: - natural-language-understanding language_creators: - expert-generated - machine-generated multilinguality: - multilingual pretty_name: Fact Completion Benchmark for Text Models size_categories: - 100K<n<1M task_categories: - text-generation - fill-mask - text2text-generation dataset_info: features: - name: dataset_id dtype: string - name: stem dtype: string - name: 'true' dtype: string - name: 'false' dtype: string - name: relation dtype: string - name: subject dtype: string - name: object dtype: string splits: - name: Bulgarian num_bytes: 14865 num_examples: 78 - name: Catalan num_bytes: 11514 num_examples: 77 - name: Croatian num_bytes: 2454 num_examples: 19 - name: Czech num_bytes: 4248 num_examples: 32 - name: Danish num_bytes: 11392 num_examples: 87 - name: Dutch num_bytes: 12067 num_examples: 81 - name: English num_bytes: 3474255 num_examples: 26254 - name: French num_bytes: 3395566 num_examples: 18395 - name: German num_bytes: 2611160 num_examples: 16287 - name: Hungarian num_bytes: 2251 num_examples: 14 - name: Italian num_bytes: 3709786 num_examples: 20448 - name: Polish num_bytes: 4472 num_examples: 29 - name: Portuguese num_bytes: 4158146 num_examples: 22974 - name: Romanian num_bytes: 2846002 num_examples: 17568 - name: Russian num_bytes: 659526 num_examples: 3289 - name: Serbian num_bytes: 3048 num_examples: 16 - name: Slovenian num_bytes: 3418 num_examples: 27 - name: Spanish num_bytes: 3175733 num_examples: 18786 - name: Swedish num_bytes: 11015 num_examples: 87 - name: Ukrainian num_bytes: 4797 num_examples: 28 download_size: 11434149 dataset_size: 24115715 language: - en - fr - es - de - uk - bg - ca - da - hr - hu - it - nl - pl - pt - ro - ru - sl - sr - sv - cs --- # Dataset Card for Fact_Completion ## Dataset Description - **Homepage:** https://bit.ly/ischool-berkeley-capstone - **Repository:** https://github.com/daniel-furman/Capstone - **Paper:** - **Leaderboard:** - **Point of Contact:** daniel_furman@berkeley.edu ### Dataset Summary This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information ``` @misc{calibragpt, author = {Shreshta Bhat and Daniel Furman and Tim Schott}, title = {CalibraGPT: The Search for (Mis)Information in Large Language Models}, year = {2023}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/daniel-furman/Capstone}}, } ``` ``` @misc{dong2022calibrating, doi = {10.48550/arXiv.2210.03329}, title={Calibrating Factual Knowledge in Pretrained Language Models}, author={Qingxiu Dong and Damai Dai and Yifan Song and Jingjing Xu and Zhifang Sui and Lei Li}, year={2022}, eprint={2210.03329}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` ``` @misc{meng2022massediting, doi = {10.48550/arXiv.2210.07229}, title={Mass-Editing Memory in a Transformer}, author={Kevin Meng and Arnab Sen Sharma and Alex Andonian and Yonatan Belinkov and David Bau}, year={2022}, eprint={2210.07229}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` ``` @inproceedings{elsahar-etal-2018-rex, title = "{T}-{RE}x: A Large Scale Alignment of Natural Language with Knowledge Base Triples", author = "Elsahar, Hady and Vougiouklis, Pavlos and Remaci, Arslen and Gravier, Christophe and Hare, Jonathon and Laforest, Frederique and Simperl, Elena", booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC} 2018)", month = may, year = "2018", address = "Miyazaki, Japan", publisher = "European Language Resources Association (ELRA)", url = "https://aclanthology.org/L18-1544", } ``` ### Contributions [More Information Needed]