{"id":"W2048359833","doi":"10.1007/s10579-007-9017-9","title":"Automatically learning semantic knowledge about multiword predicates","year":2007,"lang":"en","type":"article","venue":"Computers and the Humanities","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Computer science; Noun; Natural language processing; Linguistics; Artificial intelligence; Focus (optics); Verb","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":[0.0007042231,0.0009707012,0.0009144708,0.002753978,0.0009640708,0.002078334,0.001492165,0.001540175,0.005342354],"category_scores_gemma":[0.005992349,0.0006975938,0.001369307,0.002121081,0.0009088329,0.01103796,0.00191932,0.002619993,0.001389223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009572328,"about_ca_system_score_gemma":0.001515578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002885449,"about_ca_topic_score_gemma":0.00499276,"domain_scores_codex":[0.9991027,0.000164066,0.00009082161,0.0003816393,0.0001794795,0.00008122855],"domain_scores_gemma":[0.9960799,0.002882479,0.0002492132,0.0003604561,0.0003254919,0.0001025091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001002459,0.001119405,0.01143767,0.001250577,0.0003166085,0.001093944,0.0008692807,0.01799512,0.03068862,0.07024643,0.03196274,0.8320171],"study_design_scores_gemma":[0.0001868079,0.0003355072,0.007374087,0.0002471446,0.0003966995,0.0008934255,0.001154372,0.5751946,0.02927413,0.3618402,0.02301536,0.00008772567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3187279,0.002340171,0.6425415,0.00321041,0.0005707128,0.0002690997,0.007021143,0.01020139,0.01511755],"genre_scores_gemma":[0.7577632,0.001402336,0.2214436,0.0005328339,0.0003149894,0.0001333824,0.0149666,0.0003539252,0.003089071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005342354,"threshold_uncertainty_score":0.01787198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01257919200372212,"score_gpt":0.2518575762560514,"score_spread":0.2392783842523293,"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."}}