{"id":"W7044449237","doi":"","title":"Word Sense Disambiguation for Hungarian using Transformers","year":2020,"lang":"en","type":"other","venue":"SZTE Publicatio Repozitórium (University of Szeged)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Research, Development and Innovation Office; Atomic Energy of Canada Limited; Institute for Catastrophic Loss Reduction","keywords":"Transformer; Word-sense disambiguation; Word (group theory); Natural language","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005739306,0.0006197009,0.0009932901,0.001189029,0.0003437118,0.00008456169,0.0007570203,0.000728311,0.002069211],"category_scores_gemma":[0.000222524,0.0008564965,0.0006332063,0.001476165,0.0005049021,0.0006020185,0.0001408719,0.0004353002,0.0003897123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005034702,"about_ca_system_score_gemma":0.0006830709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002430055,"about_ca_topic_score_gemma":0.002039307,"domain_scores_codex":[0.996654,0.0001818221,0.0004769502,0.001239038,0.0007721946,0.0006759503],"domain_scores_gemma":[0.9964156,0.0001030187,0.001593512,0.001027092,0.0004187694,0.0004420289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005367149,0.0003555912,0.0002091139,0.001287898,0.001433646,0.00003210938,0.003196322,0.0000344471,0.01386862,0.003960466,0.9619489,0.01313615],"study_design_scores_gemma":[0.002010844,0.00009189756,0.0005482039,0.0002505212,0.0008970873,0.00002544986,0.002539801,0.003606061,0.0001986768,0.0001935437,0.9886615,0.0009764086],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001165685,0.0005809955,0.1484016,0.008005684,0.0008635381,0.006633729,0.007847968,0.002493713,0.8240071],"genre_scores_gemma":[0.04465683,0.0002728448,0.09381993,0.0003617292,0.00122426,0.00002351614,0.009229745,0.00423284,0.8461783],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05458167,"threshold_uncertainty_score":0.9993886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03927041289698015,"score_gpt":0.2402157953370055,"score_spread":0.2009453824400253,"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."}}