{"id":"W4389518418","doi":"10.18653/v1/2023.arabicnlp-1.15","title":"CamelParser2.0: A State-of-the-Art Dependency Parser for Arabic","year":2023,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; New York University Abu Dhabi","keywords":"Computer science; Treebank; Lexical analysis; Natural language processing; Parsing; Artificial intelligence; Dependency (UML); Modern Standard Arabic; Dependency grammar; Pipeline (software); Arabic; Python (programming language); Programming language; Linguistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002923754,0.00009775021,0.0001228129,0.00009157676,0.00007872152,0.00006059121,0.001209246,0.00004032846,0.000008750014],"category_scores_gemma":[0.0001212089,0.00006306997,0.00008926536,0.0007450127,0.00003351492,0.00030328,0.0003532573,0.00009160919,0.00005126795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001871708,"about_ca_system_score_gemma":0.00007717442,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001980056,"about_ca_topic_score_gemma":0.00004484301,"domain_scores_codex":[0.9990358,0.0000248855,0.0001921452,0.0002554908,0.0002338587,0.0002578348],"domain_scores_gemma":[0.9991159,0.0001079225,0.00008443805,0.0005391666,0.0001153125,0.00003727074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003072266,0.0001334246,0.003814556,0.000356063,0.0000665767,0.00003095376,0.002188042,0.00008740529,0.03379669,0.3081788,0.1586384,0.4926783],"study_design_scores_gemma":[0.0002852453,0.00009370148,0.0009137588,0.00007329925,0.000008542016,0.00001391981,0.00001693829,0.02646517,0.2821763,0.6800609,0.009583932,0.0003082151],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01762883,0.0003128579,0.9763649,0.002051678,0.0004196086,0.0005664559,0.000006963572,0.001579487,0.001069189],"genre_scores_gemma":[0.5265608,0.00001028048,0.4622979,0.0004372651,0.00002318513,0.00009443524,0.000002577966,0.00001538114,0.01055814],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5140671,"threshold_uncertainty_score":0.2571919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820604790219253,"score_gpt":0.2763642620750763,"score_spread":0.2581582141728837,"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."}}