{"id":"W2187008919","doi":"","title":"CUNY-BLENDER TAC-KBP2010 Entity Linking and Slot Filling System Description","year":2010,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Task (project management); Surprise; Entity linking; Sentence; Baseline (sea); Focus (optics); Space (punctuation); Natural language processing; Artificial intelligence; Information retrieval; 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":[0.002525468,0.001324497,0.001390525,0.002247117,0.001158379,0.002836688,0.003298403,0.001382981,0.0750053],"category_scores_gemma":[0.008975808,0.001151196,0.0006502809,0.001860492,0.0003936077,0.004505359,0.002273108,0.002378887,0.02505182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001834998,"about_ca_system_score_gemma":0.00279522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02254007,"about_ca_topic_score_gemma":0.02064845,"domain_scores_codex":[0.9978766,0.0003415363,0.0002603594,0.0006711886,0.0006750476,0.0001751602],"domain_scores_gemma":[0.9963696,0.00074778,0.0001575098,0.0008615539,0.001610094,0.000253409],"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":[0.0008496339,0.0003234188,0.002459618,0.001308479,0.0001244747,0.0006000301,0.000738562,0.006469268,0.02745519,0.006323975,0.5898069,0.3635405],"study_design_scores_gemma":[0.0008154989,0.0007008158,0.007761347,0.0001895234,0.0001879191,0.00168953,0.0006357299,0.2507798,0.06517176,0.006373037,0.6653,0.000395051],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.04201142,0.001318836,0.3273996,0.002311347,0.0007233361,0.004527711,0.06483368,0.5087464,0.04812767],"genre_scores_gemma":[0.177286,0.0005752427,0.5084798,0.001259074,0.0002401564,0.005424743,0.245544,0.01466259,0.04652848],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0750053,"threshold_uncertainty_score":0.2509177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01228903924965486,"score_gpt":0.2272020124718932,"score_spread":0.2149129732222383,"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."}}