{"id":"W4389945798","doi":"10.1109/wi-iat59888.2023.00023","title":"Triple Extraction with Generative Technique for Constructing Weighted Knowledge Graph","year":2023,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Knowledge graph; Computer science; Transformer; Relationship extraction; Encoder; Graph; Generative grammar; Artificial intelligence; Natural language processing; Theoretical computer science; Relation (database); Data mining","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":[0.0007593207,0.001107997,0.0006370088,0.004264683,0.0008237275,0.0008898464,0.001273542,0.000770372,0.00409514],"category_scores_gemma":[0.004261761,0.0006117527,0.001862248,0.003219213,0.0006192314,0.002597407,0.001901099,0.001431382,0.002609826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000676949,"about_ca_system_score_gemma":0.001620284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0049587,"about_ca_topic_score_gemma":0.009531655,"domain_scores_codex":[0.999074,0.0001611376,0.00008167994,0.0003632654,0.0002643693,0.00005549278],"domain_scores_gemma":[0.9985607,0.0006500859,0.0001074747,0.0003599799,0.0002839766,0.00003773726],"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":[0.0001842057,0.0001594721,0.002954512,0.0007246374,0.0002064196,0.001508004,0.001034945,0.04470371,0.03392726,0.06269272,0.02041613,0.8314879],"study_design_scores_gemma":[0.00004519847,0.0001046408,0.001507293,0.0001431704,0.0002797783,0.001083049,0.0003946522,0.6999536,0.05808314,0.1978229,0.04049375,0.00008883914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00456202,0.0001509216,0.9897568,0.0001055755,0.0000293913,0.0001446833,0.001101794,0.002998769,0.001150132],"genre_scores_gemma":[0.1391134,0.0005771928,0.8436457,0.0001956427,0.00004508067,0.0003975259,0.01160852,0.0007352312,0.003681639],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0049587,"threshold_uncertainty_score":0.01369959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03649364172802901,"score_gpt":0.2964180228597951,"score_spread":0.2599243811317661,"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."}}