{"id":"W2816262648","doi":"","title":"Farewell Freebase: Migrating the SimpleQuestions Dataset to DBpedia.","year":2018,"lang":"en","type":"article","venue":"International Conference on Computational Linguistics","topic":"Topic Modeling","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Leverage (statistics); Question answering; Knowledge graph; Information retrieval; Benchmark (surveying); Entity linking; Task (project management); Simple (philosophy); Graph; World Wide Web; Knowledge base; Theoretical computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003163234,0.0001688256,0.0001108092,0.0001456812,0.0003287831,0.0004282828,0.00162182,0.00004478699,0.0001408728],"category_scores_gemma":[0.002267076,0.000142051,0.00003944804,0.0002164641,0.00009414969,0.00008025678,0.0003868735,0.0002078154,0.0005387528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007817386,"about_ca_system_score_gemma":0.0002344229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008973041,"about_ca_topic_score_gemma":0.00008549015,"domain_scores_codex":[0.9981735,0.00006412683,0.0003685305,0.0004551209,0.0007084048,0.0002302637],"domain_scores_gemma":[0.9970835,0.0004984763,0.0001294782,0.0004791639,0.001684116,0.0001252622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006319852,0.00003680315,0.0001116563,0.000001761144,0.00001789022,0.000007912092,0.0002688887,0.0197946,0.00001889995,0.9593083,0.01699441,0.003432577],"study_design_scores_gemma":[0.0001318716,0.0000891457,0.0004035502,0.00003636598,0.000004549107,0.00000787545,0.00002991906,0.8094686,0.00007132688,0.08628757,0.1032983,0.0001709559],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001056849,0.000004930044,0.9674287,0.008967657,0.002981732,0.000169657,0.0006373204,0.0001195127,0.01863358],"genre_scores_gemma":[0.8395382,0.000001439027,0.1533947,0.004454457,0.001979951,0.00001241891,0.0004473187,0.00000940284,0.0001621026],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8730207,"threshold_uncertainty_score":0.6924757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07890198444019045,"score_gpt":0.3637709757895359,"score_spread":0.2848689913493455,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}