{"id":"W2394921060","doi":"","title":"Linguistic patterns for information extraction in ontocmaps","year":2012,"lang":"en","type":"article","venue":"International Semantic Web Conference","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Athabasca University; Royal Military College of Canada","funders":"","keywords":"Computer science; Ontology; Rule-based machine translation; Dependency (UML); Natural language processing; Ontology learning; Task (project management); Artificial intelligence; Ontology engineering; Knowledge base; Information extraction; Field (mathematics); Dependency grammar; Semantic Web; Information retrieval; Upper ontology; Suggested Upper Merged Ontology; Mathematics","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":[0.001607071,0.0005873708,0.000490997,0.003721811,0.001076308,0.002612922,0.0007525427,0.0007623229,0.005318379],"category_scores_gemma":[0.008992217,0.0004821812,0.001039979,0.00436799,0.0009542578,0.004030965,0.002316169,0.0009629999,0.002071462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005855232,"about_ca_system_score_gemma":0.001923386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002683932,"about_ca_topic_score_gemma":0.00379493,"domain_scores_codex":[0.9978415,0.0005489258,0.0003702317,0.0003597817,0.0007686737,0.0001108926],"domain_scores_gemma":[0.9965911,0.001471943,0.0002648932,0.0009375485,0.000646045,0.00008845605],"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":[0.0003611548,0.0002449104,0.009398027,0.001099184,0.0001144752,0.0012682,0.002435972,0.006549268,0.02357397,0.1331676,0.01567879,0.8061085],"study_design_scores_gemma":[0.0001466777,0.0002090225,0.007084229,0.0007113726,0.0002284329,0.00260152,0.0030117,0.1870773,0.1052287,0.450868,0.2426797,0.0001533478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04169054,0.0004236211,0.9351642,0.001161071,0.0001498848,0.0007995804,0.003392796,0.006374909,0.01084336],"genre_scores_gemma":[0.1323039,0.0004493448,0.8578434,0.0002455027,0.0000364783,0.0004791359,0.004712477,0.0006161031,0.003313594],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005318379,"threshold_uncertainty_score":0.01779175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03261506881799248,"score_gpt":0.3026057903392546,"score_spread":0.2699907215212621,"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."}}