. . . . "\u56FA\u6709\u8868\u73FE\u62BD\u51FA (\u3053\u3086\u3046\u3072\u3087\u3046\u3052\u3093\u3061\u3085\u3046\u3057\u3085\u3064, named entity extraction, named entity recognition)\u3068\u306F\u8A08\u7B97\u6A5F\u3092\u7528\u3044\u305F\u81EA\u7136\u8A00\u8A9E\u51E6\u7406\u6280\u8853\u306E\u4E00\u3064\u3067\u3042\u308A\u3001\u56FA\u6709\u540D\u8A5E(\u4EBA\u540D\u3001\u5730\u540D\u306A\u3069)\u3084\u65E5\u4ED8\u3001\u6642\u9593\u8868\u73FE\u306A\u3069\u3092\u62BD\u51FA\u3059\u308B\u6280\u8853\u3067\u3042\u308B\u3002\u60C5\u5831\u62BD\u51FA\u306E\u4E00\u5206\u91CE\u3067\u3042\u308B\u3068\u3055\u308C\u308B\u3002\""@ja . "Named entity recognition"@en . "\u56FA\u6709\u8868\u73FE\u62BD\u51FA (\u3053\u3086\u3046\u3072\u3087\u3046\u3052\u3093\u3061\u3085\u3046\u3057\u3085\u3064, named entity extraction, named entity recognition)\u3068\u306F\u8A08\u7B97\u6A5F\u3092\u7528\u3044\u305F\u81EA\u7136\u8A00\u8A9E\u51E6\u7406\u6280\u8853\u306E\u4E00\u3064\u3067\u3042\u308A\u3001\u56FA\u6709\u540D\u8A5E(\u4EBA\u540D\u3001\u5730\u540D\u306A\u3069)\u3084\u65E5\u4ED8\u3001\u6642\u9593\u8868\u73FE\u306A\u3069\u3092\u62BD\u51FA\u3059\u308B\u6280\u8853\u3067\u3042\u308B\u3002\u60C5\u5831\u62BD\u51FA\u306E\u4E00\u5206\u91CE\u3067\u3042\u308B\u3068\u3055\u308C\u308B\u3002\""@ja . . . . . . . . . . "El reconocimiento de nombres de entidades, Named entity recognition (NER), es una subtarea de la recuperaci\u00F3n de informaci\u00F3n que busca localizar y clasificar elementos at\u00F3micos en texto sobre categor\u00EDas predefinidas como nombres de personas, organizaciones, localizaciones, expresiones de horas, cantidades, valores monetarios, porcentajes, etc.\""@es . . "Named entity recognition (NER) (also known as entity identification (EI) and entity extraction) is a subtask of information extraction that seeks to locate and classify atomic elements in text into predefined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc."@en . "\u56FA\u6709\u8868\u73FE\u62BD\u51FA\""@ja . . . . . . . . "El reconocimiento de nombres de entidades, Named entity recognition (NER), es una subtarea de la recuperaci\u00F3n de informaci\u00F3n que busca localizar y clasificar elementos at\u00F3micos en texto sobre categor\u00EDas predefinidas como nombres de personas, organizaciones, localizaciones, expresiones de horas, cantidades, valores monetarios, porcentajes, etc.\n\nDesde 1998 existe un gran inter\u00E9s en el reconocimiento de entidades en las \u00E1reas de la biolog\u00EDa molecular, bioinform\u00E1tica y procesamiento del lenguaje natural.\""@es . . "Reconocimiento de nombres de entidades"@es . "Named entity recognition (NER) (also known as entity identification (EI) and entity extraction) is a subtask of information extraction that seeks to locate and classify atomic elements in text into predefined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc. \n\nFor example, a NER system producing MUC-style output might tag the sentence, \n\n:Jim bought 300 shares of Acme Corp. in 2006. \n:Jim bought 300 shares of Acme Corp. in 2006. \n\nNER systems have been created that use linguistic grammar-based techniques as well as statistical models. Hand-crafted grammar-based systems typically obtain better results, but at the cost of months of work by experienced linguists. Statistical NER systems typically require a large amount manually annotated training data.\n\nSince about 1998, there has been a great deal of interest in entity identification in the molecular biology, bioinformatics, and medical natural language processing communities. The most common entity of interest in that domain has been names of genes and gene products.\""@en . . . . . "RDF description of Named entity recognition" . . .