{"id":"W2806617565","doi":"","title":"The IBM Systems for Trilingual Entity Discovery and Linking at TAC 2015.","year":2015,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"IBM; Computer science; Natural language processing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001063081,0.00006679534,0.00009621136,0.00002679921,0.0003635414,0.0002833452,0.0003324153,0.00003670473,8.149161e-8],"category_scores_gemma":[0.00009129332,0.00004381656,0.00001588774,0.00009954719,0.0002755036,0.000325557,0.0002078296,0.00004815334,3.759649e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001286589,"about_ca_system_score_gemma":0.0000487523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001370816,"about_ca_topic_score_gemma":0.000004630114,"domain_scores_codex":[0.9994833,0.00005066791,0.0001353963,0.0001501304,0.00008598825,0.00009444396],"domain_scores_gemma":[0.9990024,0.0004578666,0.0001054675,0.000278232,0.0001215611,0.00003446842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002415365,0.000006167985,0.00004542819,0.00003998314,0.000005742674,6.392968e-8,0.0005646685,0.000001231901,0.0002885699,0.988829,0.0001203719,0.01007465],"study_design_scores_gemma":[0.0001142606,0.00003231266,0.00001008289,0.00001296862,0.00001149185,0.000009144394,0.000381345,0.000331686,0.01192097,0.9730166,0.01408185,0.00007729587],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01380163,0.03622949,0.9490621,0.0002259825,0.00006312533,0.0003767917,0.000009228051,0.000100014,0.0001316182],"genre_scores_gemma":[0.989266,0.0001676774,0.009460294,0.00001845039,0.0000788084,0.0001861598,0.000005774375,0.000004845313,0.0008119842],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9754643,"threshold_uncertainty_score":0.2796104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0126383957649103,"score_gpt":0.2859319696838521,"score_spread":0.2732935739189418,"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."}}