{"url":"/dataset/e-fb15k237","name":"E-FB15k237","full_name":null,"description_markdown":"This dataset is based on FB15k237 and a pre-trained language-model-based KGE.  The main task is to correct the wrong knowledge stored in the pre-trained model and replace the incorrect entities with alternative entities.  The model can be downloaded from [here](https://drive.google.com/drive/folders/1EOHdg8rC9iwgSyKl5RnEv9z6ATW5Ntbr?usp=share_link).","description_withheld":null,"homepage":"","introduced_date":"2023-01-19","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["E-FB15k237"],"data_loaders":[],"num_papers_in_archive":0,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}