{"id":"W4226218094","doi":"10.1145/3486622.3494010","title":"Relation Extraction with Sentence Simplification Process and Entity Information","year":2021,"lang":"en","type":"article","venue":"IEEE/WIC/ACM International Conference on Web Intelligence","topic":"Topic Modeling","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Natural language processing; Process (computing); Sentence; Relation (database); Relationship extraction; Information extraction; Artificial intelligence; Information retrieval; Programming language; Database","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":[0.001104108,0.001564886,0.00118202,0.00296437,0.000729721,0.0009780369,0.001809084,0.0008492869,0.002736687],"category_scores_gemma":[0.004253936,0.0004759705,0.001478604,0.002965041,0.0005151871,0.00315424,0.001312419,0.001556133,0.002027086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006028906,"about_ca_system_score_gemma":0.001447245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006170884,"about_ca_topic_score_gemma":0.01047985,"domain_scores_codex":[0.9989312,0.0002081862,0.0001491749,0.0003958042,0.0002601821,0.0000553096],"domain_scores_gemma":[0.9982889,0.0007167854,0.0001840299,0.0003683075,0.0004020864,0.00003982265],"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":[0.0003473565,0.0002652314,0.002166,0.0008186299,0.0002145667,0.0008345211,0.0006291834,0.03031429,0.0488897,0.006506427,0.01841998,0.8905942],"study_design_scores_gemma":[0.00008424648,0.0002628705,0.003733697,0.000104215,0.0003865025,0.0009108465,0.0003388972,0.8540589,0.08192243,0.01616764,0.04193028,0.00009951105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02846306,0.001245176,0.9553074,0.0004312957,0.000170028,0.0004863741,0.002331058,0.009113824,0.002451814],"genre_scores_gemma":[0.1474064,0.001009894,0.8309056,0.0003065616,0.0001730471,0.0003686122,0.01414938,0.0003457358,0.0053349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006170884,"threshold_uncertainty_score":0.01226991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05525394880722037,"score_gpt":0.3218998359069743,"score_spread":0.2666458870997539,"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."}}