{"id":"W2131809738","doi":"10.1080/01690960344000152","title":"Admitting that admitting verb sense into corpus analyses makes sense","year":2004,"lang":"en","type":"article","venue":"Language and Cognitive Processes","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Verb; Meaning (existential); Linguistics; Ambiguity; Consistency (knowledge bases); Psychology; Exploit; Computer science; Natural language processing; Artificial intelligence; Philosophy","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":[0.04982642,0.001510735,0.001366364,0.003835478,0.002955599,0.01077184,0.003259821,0.002512062,0.004551259],"category_scores_gemma":[0.2537901,0.001047883,0.0009500522,0.00340566,0.009392519,0.01562845,0.005949214,0.006746686,0.001635146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008721619,"about_ca_system_score_gemma":0.00203957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001384408,"about_ca_topic_score_gemma":0.003705454,"domain_scores_codex":[0.96137,0.02184101,0.004238483,0.005147326,0.0067455,0.000657692],"domain_scores_gemma":[0.8189863,0.1137482,0.01156815,0.04474482,0.01001649,0.0009360249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004322728,0.0001885799,0.03717981,0.001319769,0.0009088657,0.001115482,0.02634599,0.002320729,0.02207977,0.6390116,0.03359872,0.2354985],"study_design_scores_gemma":[0.00003273151,0.0001023991,0.008170146,0.0003264066,0.0001702893,0.001099606,0.004117486,0.01074909,0.006355741,0.8993974,0.06936923,0.0001095823],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0804068,0.001830895,0.8627625,0.02625454,0.005253189,0.0002801277,0.001462558,0.001754086,0.01999539],"genre_scores_gemma":[0.6876191,0.000916393,0.29081,0.008336926,0.002732617,0.0008787126,0.001567676,0.001301428,0.005837016],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04982642,"threshold_uncertainty_score":0.2635105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0252927054938304,"score_gpt":0.3218864663115489,"score_spread":0.2965937608177185,"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."}}