{"id":"W3098980613","doi":"10.18653/v1/2020.emnlp-main.304","title":"Recurrent Interaction Network for Jointly Extracting Entities and Classifying Relations","year":2020,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Beijing Advanced Innovation Center for Big Data and Brain Computing; Fundamental Research Funds for the Central Universities; State Key Laboratory of Software Development Environment; National Natural Science Foundation of China","keywords":"Computer science; Task (project management); Relation (database); Artificial intelligence; Machine learning; Multi-task learning; Relationship extraction; Task analysis; Joint (building); 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":[0.001195001,0.00125048,0.0008358334,0.002025388,0.0004554505,0.0008905936,0.001415375,0.0009743162,0.001764142],"category_scores_gemma":[0.003103645,0.0004048477,0.001202182,0.002093438,0.0004796428,0.002570635,0.001092022,0.001340249,0.0008842723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009482612,"about_ca_system_score_gemma":0.0007749607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007856573,"about_ca_topic_score_gemma":0.009911601,"domain_scores_codex":[0.9991424,0.000240629,0.00004361954,0.0003096868,0.0001687237,0.00009485733],"domain_scores_gemma":[0.9989329,0.000552939,0.0001760743,0.0001254859,0.0001699983,0.00004249292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005643537,0.0002735346,0.005860663,0.0002698526,0.0003410638,0.000508888,0.0004177406,0.6041176,0.0168938,0.03788631,0.01266323,0.3202029],"study_design_scores_gemma":[0.000004530925,0.00001984279,0.0005435431,0.000005488394,0.00003038216,0.0000349946,0.00001113087,0.986602,0.001238496,0.01021515,0.001284428,0.00001002881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02898404,0.0008565173,0.9647835,0.0003610701,0.00006997019,0.00007392588,0.0008173623,0.001507201,0.00254644],"genre_scores_gemma":[0.7327457,0.001087307,0.2494722,0.0002492353,0.0002073737,0.0003495594,0.006093619,0.0002467134,0.009548226],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007856573,"threshold_uncertainty_score":0.01562172,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1047991926442555,"score_gpt":0.2967338189729715,"score_spread":0.1919346263287161,"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."}}