{"id":"W4389519516","doi":"10.18653/v1/2023.emnlp-main.955","title":"Anaphor Assisted Document-Level Relation Extraction","year":2023,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Fundamental Research Funds for the Central Universities; State Key Laboratory of Software Development Environment","keywords":"Computer science; Relationship extraction; Focus (optics); Graph; Natural language processing; Relation (database); Sentence; Artificial intelligence; Information retrieval; Information extraction; Theoretical computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002216005,0.00004734259,0.00004418803,0.0001054944,0.00006969851,0.00008684983,0.0001949921,0.00003727873,0.00004784079],"category_scores_gemma":[0.00002600536,0.00004381878,0.0000243731,0.0004253809,0.000004003929,0.000582536,0.0000742277,0.00005801524,0.0004594802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003656013,"about_ca_system_score_gemma":0.00001845261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005788995,"about_ca_topic_score_gemma":0.00001955062,"domain_scores_codex":[0.9993457,0.00002301659,0.0001261763,0.0002029707,0.000175629,0.0001265657],"domain_scores_gemma":[0.9995816,0.0000425874,0.00003395983,0.0002803078,0.00002756958,0.0000339617],"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":[0.000003958373,0.00002869345,0.002078397,0.00001197927,0.00002043017,0.00002554203,0.0005984696,0.004378602,0.009164924,0.3210438,0.01105027,0.6515949],"study_design_scores_gemma":[0.0002545705,0.00001555659,0.1603039,0.000007628009,0.000002306648,0.00001004176,0.0000354983,0.8203603,0.001347256,0.01115506,0.006381036,0.0001268076],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04501737,0.00000558983,0.9426417,0.001650681,0.000467509,0.00006214136,2.152146e-7,0.0005882361,0.009566585],"genre_scores_gemma":[0.9006568,0.000005866957,0.08839645,0.0001248262,0.00005037643,0.000007937479,0.000004341205,0.000003992708,0.01074945],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8556394,"threshold_uncertainty_score":0.5905842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08087274730028714,"score_gpt":0.3144574903102856,"score_spread":0.2335847430099985,"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."}}