{"id":"W2916680872","doi":"","title":"THUNLP at TAC KBP 2013 in Entity Linking","year":2013,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Task (project management); Computer science; Entity linking; Natural language processing; Artificial intelligence; F1 score; Knowledge base; Engineering","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":[0.01186185,0.002487611,0.001887319,0.004108128,0.004054061,0.005197801,0.003384398,0.002988572,0.03140913],"category_scores_gemma":[0.01802216,0.001330009,0.001221892,0.004546714,0.0008622836,0.01010091,0.006996715,0.003806553,0.05054991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001903751,"about_ca_system_score_gemma":0.002852214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02273858,"about_ca_topic_score_gemma":0.02392762,"domain_scores_codex":[0.9881192,0.004535953,0.0008603159,0.002724516,0.0028034,0.0009566867],"domain_scores_gemma":[0.9879135,0.003271624,0.0003168929,0.003066892,0.004359597,0.001071479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001852994,0.001111733,0.003979109,0.001279696,0.0002806553,0.001152651,0.002497436,0.004172937,0.02568054,0.003432887,0.6163504,0.338209],"study_design_scores_gemma":[0.001045278,0.001491302,0.01522406,0.0003362318,0.0004221449,0.002433512,0.002379413,0.09483673,0.1172555,0.008091778,0.7559062,0.000577834],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.09834956,0.005023728,0.2789453,0.00480511,0.005552922,0.002971978,0.08270019,0.4328743,0.08877708],"genre_scores_gemma":[0.2184485,0.001171748,0.3329617,0.002089943,0.0009179983,0.002289462,0.343334,0.02833096,0.07045566],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03140913,"threshold_uncertainty_score":0.105074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009270023607219102,"score_gpt":0.2306121815772403,"score_spread":0.2213421579700212,"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."}}