{"id":"W2251970502","doi":"10.63317/37r3xzsc3g5u","title":"Linked Open Data and Web Corpus Data for noun compound bracketing","year":2014,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Bracketing (phenomenology); Computer science; Linked data; Task (project management); Noun; World Wide Web; Information retrieval; Open data; Resource (disambiguation); Natural language processing; Semantic Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"bench_or_experimental","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003667364,0.0006068167,0.0007518246,0.00881945,0.00203935,0.003667888,0.001343636,0.001336218,0.01145734],"category_scores_gemma":[0.02454778,0.000675209,0.001016091,0.008706836,0.001192066,0.007112958,0.00352871,0.002426604,0.00701322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001506227,"about_ca_system_score_gemma":0.004009039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01474185,"about_ca_topic_score_gemma":0.02378819,"domain_scores_codex":[0.9957774,0.001088796,0.000539841,0.0008261391,0.001574808,0.0001930668],"domain_scores_gemma":[0.9832644,0.007155842,0.0009450834,0.004655032,0.003415358,0.0005642635],"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":[0.001610203,0.0009307498,0.02458263,0.002272279,0.0002729857,0.001796966,0.004328197,0.01486499,0.02700451,0.2352033,0.1975978,0.4895355],"study_design_scores_gemma":[0.0001981245,0.0002100267,0.02358889,0.0006269888,0.0002277348,0.001266443,0.003608712,0.2350507,0.0464273,0.1801116,0.5083754,0.0003080153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.109012,0.001918035,0.561596,0.003516161,0.0009918052,0.001049016,0.2549663,0.03682598,0.0301246],"genre_scores_gemma":[0.2418822,0.0009691241,0.4112967,0.0003491381,0.000256838,0.001287924,0.3295449,0.003316951,0.01109617],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01474185,"threshold_uncertainty_score":0.03832859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08505609058429106,"score_gpt":0.3571034207995201,"score_spread":0.2720473302152291,"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."}}