{"id":"W4293920114","doi":"10.54097/hset.v12i.1368","title":"The Advance of Deep Learning Based Named Entity Recognition","year":2022,"lang":"en","type":"article","venue":"Highlights in Science Engineering and Technology","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Named-entity recognition; Computer science; Artificial intelligence; Deep learning; Entity linking; Named entity; Variety (cybernetics); Natural language processing; Artificial neural network; Machine learning; Knowledge base; Task (project management)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001819601,0.0008657834,0.001045273,0.00137467,0.000313959,0.001730874,0.001684548,0.001125257,0.002359431],"category_scores_gemma":[0.003685005,0.000370169,0.0008984653,0.002401651,0.0007168364,0.007279919,0.001242092,0.002474042,0.001874006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001101036,"about_ca_system_score_gemma":0.0009472155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003790287,"about_ca_topic_score_gemma":0.002998611,"domain_scores_codex":[0.9988726,0.0003223634,0.000086227,0.0003263279,0.0003084664,0.00008395761],"domain_scores_gemma":[0.9984376,0.0005935486,0.0001233467,0.0003623317,0.0004296145,0.00005358346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001089351,0.0001005495,0.002755201,0.0006366307,0.0001902525,0.0001681536,0.0002000575,0.0608487,0.01033327,0.08964533,0.02864278,0.8063701],"study_design_scores_gemma":[0.000008851831,0.00004396535,0.001187268,0.0001025422,0.00007921608,0.000154727,0.00007264009,0.8426191,0.01167708,0.08106147,0.06293355,0.00005960789],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.009178638,0.01468763,0.9622498,0.003252181,0.000569993,0.00003677613,0.00076627,0.002555494,0.006703186],"genre_scores_gemma":[0.437507,0.03814336,0.4968189,0.002191741,0.001495201,0.0001437917,0.006930629,0.0004714935,0.01629794],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003790287,"threshold_uncertainty_score":0.009623051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006035953314598795,"score_gpt":0.1996807815675929,"score_spread":0.1936448282529941,"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."}}