{"id":"W3037085112","doi":"10.18653/v1/2020.repl4nlp-1.23","title":"Supertagging with CCG primitives","year":2020,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Lexicalization; Computer science; Natural language processing; Artificial intelligence; Parsing; Word (group theory); Part of speech; Rule-based machine translation; Task (project management); Sentence; Linguistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00187044,0.0007340714,0.0006660488,0.001565633,0.0008304992,0.001215114,0.00195197,0.001181099,0.006322586],"category_scores_gemma":[0.007098848,0.0006043541,0.0009609935,0.002087702,0.002153293,0.003256632,0.003261491,0.002361896,0.002947258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00095997,"about_ca_system_score_gemma":0.001888892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003705937,"about_ca_topic_score_gemma":0.007816987,"domain_scores_codex":[0.9981377,0.0005642439,0.0001219989,0.0005527842,0.0004561793,0.0001670992],"domain_scores_gemma":[0.993829,0.002388271,0.0002274367,0.002781498,0.0006123694,0.0001614288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005478881,0.0002062913,0.004439441,0.0005113045,0.00008069436,0.0009170859,0.002477653,0.05258248,0.06312086,0.2962216,0.02905069,0.549844],"study_design_scores_gemma":[0.00006030575,0.00008980682,0.0008445944,0.00007969847,0.00004770686,0.0003624529,0.000227521,0.4180456,0.03260659,0.4883192,0.05924096,0.00007541425],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01975472,0.0001408169,0.9634935,0.0002858586,0.0001337201,0.000173075,0.0006112109,0.0106304,0.004776678],"genre_scores_gemma":[0.3586886,0.0001482381,0.6288727,0.0006988333,0.00010071,0.0003589304,0.00208274,0.003284707,0.005764622],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006322586,"threshold_uncertainty_score":0.02115119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01393717394215412,"score_gpt":0.2319330178308518,"score_spread":0.2179958438886976,"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."}}