{"url":"/sota/columns-property-annotation-on-wdc-sotab-v2","task":{"name":"Columns Property Annotation","url":"/task/columns-property-annotation","note":null},"dataset":{"name":"WDC SOTAB V2","url":"/dataset/wdc-sotab-v2"},"category":"Natural Language Processing","categories":["Knowledge Base","Natural Language Processing"],"category_note":null,"description":"**Column Property Annotation** (CPA) refers to the task of predicting the semantic relation between two columns and is a subtask of [Table Annotation](https://paperswithcode.com/task/table-annotation). The input of a CPA problem is most commonly a pair of columns, but can also be only one column. The labels used in CPA are properties from vocabularies. Some examples are *name*, *price*, *datePublished* etc.\r\n\r\nCPA is usually a multi-class classification problem and is also referred to as column relation annotation or relation extraction in different works.","description_from":"task","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","rank":"the archive's row order at snapshot; not re-ranked","rows_end_at":"2025-07-28","rows_withheld_as_spam":0,"metric_values":"the archive's strings, untouched"},"metrics":["Micro F1"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"Micro F1":"higher"}},"counts":{"rows":4,"rows_with_code":0,"rows_with_paper_page":4,"rows_dated":4,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"TorchicTab","metrics":{"Micro F1":"87.11"},"uses_additional_data":false,"paper_date":"2023-11-20","paper":"/paper/torchictab-semantic-table-annotation-with","paper_url":"https://www.csd.uoc.gr/~vefthym/SemTab2023/paper2.pdf","paper_title":"TorchicTab: Semantic Table Annotation with Wikidata and Language Models","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":2,"model":"MUT2KG","metrics":{"Micro F1":"79.35"},"uses_additional_data":false,"paper_date":"2023-11-20","paper":"/paper/semantic-annotation-of-tabular-data-for","paper_url":"https://ceur-ws.org/Vol-3557/paper5.pdf","paper_title":"Semantic Annotation of Tabular Data for Machine-to-Machine Interoperability via Neuro-Symbolic Anchoring","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":3,"model":"TSOTSA","metrics":{"Micro F1":"23.55"},"uses_additional_data":false,"paper_date":"2023-11-20","paper":"/paper/exploring-naive-bayes-classifiers-for-tabular","paper_url":"https://ceur-ws.org/Vol-3557/paper6.pdf","paper_title":"Exploring Naive Bayes Classifiers for Tabular Data to Knowledge Graph Matching","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":4,"model":"DREIFLUSS","metrics":{"Micro F1":"17.39"},"uses_additional_data":false,"paper_date":"2023-11-20","paper":"/paper/dreifluss-a-minimalist-approach-for-table","paper_url":"https://ceur-ws.org/Vol-3557/paper4.pdf","paper_title":"DREIFLUSS: A Minimalist Approach for Table Matching","code":null,"n_code_links":0,"syntology":null}],"since_archive":{"claim":"Results that newer papers report for their own method, placed here by Syntology. A model pointed at the cell in the paper's own table; the number was read from that cell and checked against this leaderboard's metric, dataset, split and scale; an independent check that saw this leaderboard's other rows and every other leaderboard on the same dataset accepted it. Not reviewed by the paper's authors or by the archive's editors, and not ranked against the archive rows.","extraction_file_present":true,"measurement":{"test_papers":883,"papers_with_output":881,"judged_true":108,"judged":110,"wilson95_lower":0.9361,"measured_on":"2026-09-24","frozen_commit":"0e3de0df94"},"measurement_note":"blind adjudication of accepted entries on a held-out split of archive papers, rules frozen before the test","coverage":{"sentence":"Syntology has checked 6,795 of the 9,581 papers on this site that are newer than the archive; results from the others appear after they are checked.","complete":false,"papers_newer_than_archive":9581,"papers_checked":6795,"papers_extracted_not_yet_verified":0,"boards_without_verdict":2,"papers_not_yet_extracted":2785},"order":"newest first by month (arXiv date, else the arXiv-id month), then arXiv id descending","columns":[],"entries":[]},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per row: N of M harvested code samples from that row's paper executed on a synthesized fixture; the other M-N are unverified. Not a reproduction of the row's number; not a correctness claim. n_pointer_only_licence counts samples the site points at rather than redistributes (a licence axis, independent of ran/unverified).","rows_with_graph_line":0,"rows_with_any_sample_ran":0,"distinct_papers_with_graph_line":0,"distinct_papers_with_any_sample_ran":0,"samples_over_distinct_papers":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"row-weighted: a paper behind several rows is counted once per row; inflated relative to samples_over_distinct_papers by design, kept for readers summing the per-row syntology blocks"}}}