{"id":"W2400099212","doi":"","title":"ITNLP 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; Ranking (information retrieval); Cluster analysis; Entity linking; Information retrieval; Set (abstract data type); Knowledge base; Task (project management); Rank (graph theory); Population; Artificial intelligence; Process (computing); Hierarchical clustering; Data mining; Natural language processing; Mathematics; 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":[0.005644285,0.001902137,0.001307249,0.004627741,0.002819603,0.00425929,0.003673287,0.00192828,0.04126908],"category_scores_gemma":[0.01083241,0.0009318583,0.0009589256,0.005620791,0.0005373097,0.007883014,0.003279304,0.003396924,0.04146326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00217081,"about_ca_system_score_gemma":0.00416701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01899266,"about_ca_topic_score_gemma":0.01961245,"domain_scores_codex":[0.9963768,0.0008599298,0.0003017455,0.0007463569,0.001395196,0.0003200832],"domain_scores_gemma":[0.9938765,0.00121631,0.0003130577,0.001692699,0.002397451,0.0005040704],"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":[0.0004538509,0.0004022295,0.001206968,0.0004995507,0.0001216612,0.0006990307,0.0005339573,0.003339499,0.005962744,0.01271465,0.8749635,0.09910233],"study_design_scores_gemma":[0.0002558146,0.0001570261,0.002188525,0.0001104442,0.0001422764,0.0005665934,0.0004024377,0.04332006,0.02213505,0.01420297,0.9163885,0.0001303569],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.01989895,0.001037776,0.2774179,0.002583537,0.001750724,0.001581324,0.2758389,0.3128603,0.1070306],"genre_scores_gemma":[0.03693482,0.0003020129,0.2003223,0.000690239,0.0001834589,0.0009281712,0.7221816,0.01135124,0.02710619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04126908,"threshold_uncertainty_score":0.1380589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005544463551831476,"score_gpt":0.233324954191289,"score_spread":0.2277804906394575,"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."}}