{"url":"/sota/knowledge-graph-completion-on-dbbook2014","task":{"name":"Knowledge Graph Completion","url":"/task/knowledge-graph-completion","note":null},"dataset":{"name":"DBbook2014","url":null},"category":"Natural Language Processing","categories":["Graphs","Knowledge Base","Natural Language Processing"],"category_note":null,"description":"Knowledge graphs $G$ are represented as a collection of triples $\\\\{(h, r, t)\\\\}\\subseteq E\\times R\\times E$, where $E$ and $R$ are the entity set and relation set. The task of **Knowledge Graph Completion** is to either predict unseen relations $r$ between two existing entities: $(h, ?, t)$ or predict the tail entity $t$ given the head entity and the query relation: $(h, r, ?)$.\r\n\r\n\r\n<span class=\"description-source\">Source: [One-Shot Relational Learning for Knowledge Graphs ](https://arxiv.org/abs/1808.09040)</span>","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":["Hits@10","Mean Rank"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"Hits@10":null,"Mean Rank":null}},"counts":{"rows":1,"rows_with_code":1,"rows_with_paper_page":1,"rows_dated":1,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"KTUP (soft)","metrics":{"Hits@10":"60.75","Mean Rank":"499"},"uses_additional_data":false,"paper_date":"2019-02-17","paper":"/paper/unifying-knowledge-graph-learning-and","paper_url":"http://arxiv.org/abs/1902.06236v1","paper_title":"Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences","code":"https://github.com/TaoMiner/joint-kg-recommender","n_code_links":1,"syntology":null}],"since_archive":{"present":false,"note":"No Syntology-extracted rows are published in this build."},"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"}}}