--- language: - en license: - cc-by-sa-4.0 - cc-by-nc-4.0 multilinguality: - monolingual pretty_name: FTRACE size_categories: - 1M\".", "targets_pretokenized": " South Asia", "page_uri": "Q33199", "masked_uri": "Q771405", "masked_type": "subject", "example_uris": "Q33199-1-Q48-Q771405-1", "facts": "P361,Q48,Q771405;P30,Q48,Q771405", "id": 8} ``` #### Queries - **Size of downloaded dataset files:** 1.7 MB - **Size of the generated dataset:** 8.9 MB - **Total amount of disk used:** 10.6 MB An example of 'query' looks as follows. ``` {"inputs_pretokenized": "Paul Ehrlich used to work in .", "targets_pretokenized": " Frankfurt", "uuid": "5b063008-a8ba-4064-9f59-e70102bb8c50", "obj_uri": "Q1794", "sub_uri": "Q57089", "predicate_id": "P937", "obj_surface": "Frankfurt", "sub_surface": "Paul Ehrlich"} ``` ### Data Fields The data fields are the same among all splits. #### Abstracts - `inputs_pretokenized`: a `string` feature. - `targets_pretokenized`: a `string` feature. - `masked_uri`: a `string` feature. - `masked_type`: a `string` feature. - `facts`: a `string` feature. - `id`: a `string` feature. - `example_uris`: a `string` feature. - `page_uri`: a `string` feature. #### Queries - `inputs_pretokenized`: a `string` feature. - `targets_pretokenized`: a `string` feature. - `obj_surface`: a `string` feature. - `sub_surface`: a `string` feature. - `obj_uri`: a `string` feature. - `sub_uri`: a `string` feature. - `predicate_id`: a `string` feature. - `uuid`: a `string` feature. ### Data Splits | name | train | |-----------|------:| |Abstracts |1560453| |Queries |31479 | ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data LAMA: https://github.com/facebookresearch/LAMA TRex: https://hadyelsahar.github.io/t-rex/ #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information The parts of this dataset are available under the [Creative Commons Attribution-ShareAlike License (CC BY-SA 4.0)](https://creativecommons.org/licenses/by-sa/4.0/) and [The Creative Commons Attribution-Noncommercial 4.0 International License](https://github.com/facebookresearch/LAMA/blob/master/LICENSE) ### Citation Information The main paper should be cited as follow: ``` @misc{https://doi.org/10.48550/arxiv.2205.11482, doi = {10.48550/ARXIV.2205.11482}, url = {https://arxiv.org/abs/2205.11482}, author = {Akyürek, Ekin and Bolukbasi, Tolga and Liu, Frederick and Xiong, Binbin and Tenney, Ian and Andreas, Jacob and Guu, Kelvin}, keywords = {Computation and Language (cs.CL), Information Retrieval (cs.IR), FOS: Computer and information sciences, FOS: Computer and information sciences}, title = {Tracing Knowledge in Language Models Back to the Training Data}, publisher = {arXiv}, year = {2022}, } ``` Please also cite Petroni et al., 2019 for the query set, and Elsahar et al., 2018 for the abstract set. ``` @inproceedings{petroni2019language, title={Language Models as Knowledge Bases?}, author={F. Petroni, T. Rockt{\"{a}}schel, A. H. Miller, P. Lewis, A. Bakhtin, Y. Wu and S. Riedel}, booktitle={In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019}, year={2019} } ``` ``` @inproceedings{elsahar2018t, title={T-rex: 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)}, year={2018} } ``` ### Contributions