{"url":"/dataset/i-phi","name":"I.PHI","full_name":null,"description_markdown":"**I.PHI** processes the Packard Humanities Institute (PHI) database of ancient Greek inscriptions including the geographical and chronological metadata into a machine actionable format. The processed dataset is referred to as I.PHI.","description_withheld":null,"homepage":"https://github.com/sommerschield/iphi","introduced_date":"2022-03-09","introduced_date_note":null,"introduced_by":{"paper":"/paper/restoring-and-attributing-ancient-texts-using","title":"Restoring and attributing ancient texts using deep neural networks","first_author":"Yannis Assael","url":null},"license":{"name":"Custom","url":"https://github.com/sommerschield/iphi#license"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Ancient Text Restoration","url":"/task/ancient-tex-restoration","datasets_with_task":"/datasets/task/ancient-tex-restoration"}],"languages":[],"variants":["I.PHI"],"data_loaders":[{"repo":"https://github.com/sommerschield/iphi","url":"https://github.com/sommerschield/iphi","frameworks":[]}],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/ancient-text-restoration-on-i-phi","task":"Ancient Text Restoration","dataset_variant":"I.PHI","rows":5,"metrics":["CER (%)","Top 1 (%)","Top 20 (%)","Region (Top 1 (%))","Region (Top 3 (%))","Date (Years)"],"first_row_in_archive_order":{"model":"Ancient historian and Ithaca","paper":"/paper/restoring-and-attributing-ancient-texts-using","metrics":{"CER (%)":"18.3","Top 1 (%)":"71.7","Top 20 (%)":"78.3"},"code_links":[{"title":"deepmind/ithaca","url":"https://github.com/deepmind/ithaca"},{"title":"sommerschield/iphi","url":"https://github.com/sommerschield/iphi"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/restoring-and-attributing-ancient-texts-using","title":"Restoring and attributing ancient texts using deep neural networks","date":"2022-03-09","rows_on_this_dataset":5,"code_links":2,"syntology":null}],"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."}