{"id":"W3174860526","doi":"10.18653/v1/2021.findings-acl.128","title":"Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction","year":2021,"lang":"en","type":"article","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"National Key Research and Development Program of China","keywords":"Computer science; Natural language processing; Artificial intelligence; Sentence; Sentiment analysis; Inference; ENCODE; Graph; Exploit; Ontology; Pipeline (software); Theoretical computer science","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":[0.0004751848,0.00153948,0.0007801719,0.001895397,0.0004710754,0.000848734,0.0007900734,0.0007772335,0.003862905],"category_scores_gemma":[0.001776276,0.0003773286,0.001448198,0.001464233,0.0002887859,0.002166363,0.001173053,0.001255132,0.00248591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004930389,"about_ca_system_score_gemma":0.0007706482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002167357,"about_ca_topic_score_gemma":0.004967506,"domain_scores_codex":[0.9996202,0.00005757726,0.00003449103,0.0001269336,0.0001123314,0.00004849472],"domain_scores_gemma":[0.9995683,0.0001004846,0.00005974469,0.00007357291,0.0001758429,0.00002206036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004220798,0.0002685393,0.005393268,0.0006511103,0.0002485829,0.001010031,0.0003845464,0.02269568,0.1167297,0.01499836,0.05115873,0.7860394],"study_design_scores_gemma":[0.00005962279,0.0001749132,0.005687031,0.00007292358,0.0001917497,0.0006209147,0.0002876975,0.8629124,0.0516543,0.04676827,0.03149462,0.00007547097],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05256576,0.0007427113,0.9175859,0.000680896,0.000315116,0.0003998603,0.005945621,0.01119464,0.01056951],"genre_scores_gemma":[0.4376231,0.0006888303,0.5281227,0.0004810491,0.0002387194,0.0003470732,0.02231373,0.0007691077,0.009415827],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003862905,"threshold_uncertainty_score":0.01292276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01717425674907036,"score_gpt":0.277706360302578,"score_spread":0.2605321035535076,"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."}}