{"id":"W2184852068","doi":"","title":"The CASIA Entity linking System at TAC 2013","year":2013,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Entity linking; Cluster analysis; String (physics); Task (project management); Matching (statistics); Knowledge base; Information retrieval; Hierarchical clustering; Variety (cybernetics); Rank (graph theory); Data mining; Base (topology); Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004803965,0.001470122,0.001310206,0.006552218,0.002712579,0.004262847,0.003474484,0.00161707,0.02147568],"category_scores_gemma":[0.008643091,0.0007213631,0.0009947148,0.004402888,0.0006061965,0.008462079,0.003147746,0.002682355,0.01804517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003387358,"about_ca_system_score_gemma":0.004592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02798617,"about_ca_topic_score_gemma":0.02718052,"domain_scores_codex":[0.9968465,0.0007348289,0.000298497,0.0007651797,0.001137239,0.0002177693],"domain_scores_gemma":[0.9944225,0.0009850716,0.0003127941,0.001575248,0.002195601,0.0005088056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009343564,0.0004037728,0.00261232,0.0008823689,0.0002352896,0.001230229,0.0006080895,0.003754382,0.01250704,0.0199177,0.7226089,0.2343055],"study_design_scores_gemma":[0.0003219263,0.000163716,0.004244064,0.0001524981,0.0002854588,0.001263665,0.0005729494,0.07353622,0.03044159,0.01499474,0.8737428,0.0002804461],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.03820476,0.002887403,0.2879292,0.003693993,0.001604052,0.001960731,0.07964496,0.4499404,0.1341345],"genre_scores_gemma":[0.1410378,0.001293134,0.4909546,0.002010346,0.0005560282,0.001806005,0.3073205,0.01273131,0.04229029],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02798617,"threshold_uncertainty_score":0.07184327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005015511076475368,"score_gpt":0.2322320328606323,"score_spread":0.2272165217841569,"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."}}