{"id":"W159720989","doi":"10.1007/978-3-642-25324-9_25","title":"Modular Natural Language Processing Using Declarative Attribute Grammars","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Logic, programming, and type systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; L-attributed grammar; Programming language; Executable; Context-free grammar; Extended Affix Grammar; Unification; Rule-based machine translation; S-attributed grammar; Parsing; Natural language processing; Parsing expression grammar; Syntax; Definite clause grammar; Artificial intelligence; Abstract syntax; Metalanguage; Modular design; Semantics (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":[0.001212938,0.0006112579,0.0007824628,0.0008440337,0.0006141622,0.002372631,0.002136226,0.0005851528,0.006383126],"category_scores_gemma":[0.002374545,0.0007248883,0.002120342,0.001015159,0.001296583,0.004491287,0.002445149,0.001648681,0.002535659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004442946,"about_ca_system_score_gemma":0.0006709727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000809049,"about_ca_topic_score_gemma":0.001368897,"domain_scores_codex":[0.9991686,0.0001512403,0.00009326819,0.0002087879,0.0002884822,0.0000896064],"domain_scores_gemma":[0.9985447,0.0007184212,0.00006850269,0.0004655402,0.000158675,0.00004424537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002445268,0.0002371734,0.0009183364,0.0005317123,0.0001178406,0.0005052472,0.001088318,0.02897438,0.04998669,0.4545838,0.01535885,0.4474532],"study_design_scores_gemma":[0.00009054769,0.00008846248,0.0004389515,0.0000880342,0.0001248279,0.0004678701,0.0001574317,0.191754,0.06253589,0.6923565,0.0518207,0.00007679519],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009567636,0.0001376464,0.9786573,0.0001146388,0.00004675941,0.00006526167,0.0001961598,0.008181105,0.003033549],"genre_scores_gemma":[0.1799792,0.000392668,0.8070173,0.0001831996,0.000106702,0.000159198,0.002029572,0.002267158,0.007864942],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006383126,"threshold_uncertainty_score":0.02135366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03464108760745817,"score_gpt":0.2653546580979275,"score_spread":0.2307135704904693,"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."}}