@prefix owl:	<http://www.w3.org/2002/07/owl#> .
@prefix dbpedia:	<http://dbpedia.org/resource/> .
dbpedia:Named_entity_recognition	owl:sameAs	<http://rdf.freebase.com/ns/guid.9202a8c04000641f800000000062a2b9> .
@prefix foaf:	<http://xmlns.com/foaf/0.1/> .
@prefix ns3:	<http://en.wikipedia.org/wiki/> .
dbpedia:Named_entity_recognition	foaf:page	ns3:Named_entity_recognition .
@prefix dbpprop:	<http://dbpedia.org/property/> .
@prefix ns5:	<http://isoft.postech.ac.kr/Research/Bio/bio.html#> .
dbpedia:Named_entity_recognition	dbpprop:reference	ns5:Requirements ,
		<http://www.cnts.ua.ac.be/conll/> ,
		<http://mallet.cs.umass.edu/> ,
		<http://gate.ac.uk/> ,
		<http://kmi.open.ac.uk/people/jianhan/ESpotter/> ,
		<http://www.hgc.ims.u-tokyo.ac.jp/service/tooldoc/KeX/intro.html> ,
		<http://bcsp1.iis.sinica.edu.tw/aiiagmt/> ,
		<http://www.cs.wisc.edu/~bsettles/abner/> ,
		<http://garraf.epsevg.upc.es/freeling/demo.php> ,
		<http://garraf.epsevg.upc.es/freeling/> ,
		<http://www.cs.technion.ac.il/~gabr/resources/data/ne_datasets.html> ,
		<http://gate.ac.uk/ie/annie.html> ,
		<http://minorthird.sourceforge.net/> ,
		<http://l2r.cs.uiuc.edu/~cogcomp/software.php> ,
		<http://nlp.cs.nyu.edu/ene/> ,
		<http://www.lrec-conf.org/> ,
		<http://www.ldc.upenn.edu/Catalog/docs/LDC2005T33/BBN-Types-Subtypes.html> ,
		<http://balie.sourceforge.net/> ,
		<http://www.digitalsonata.com/demo.aspx?component=morphoLogic> ,
		<http://bionlp.sourceforge.net> .
@prefix rdfs:	<http://www.w3.org/2000/01/rdf-schema#> .
dbpedia:Named_entity_recognition	rdfs:label	"\u56FA\u6709\u8868\u73FE\u62BD\u51FA"@ja ,
		"Reconocimiento de nombres de entidades"@es ,
		"Named entity recognition"@en ,
		"Entit\u00E9s nomm\u00E9es"@fr ;
	dbpprop:abstract	"\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\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 (NER) (also known as entity identification 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. Most research on NER systems has been structured as taking an unannotated block of text, such as this one: Jim bought 300 shares of Acme Corp. in 2006. And producing an annotated block of text, such as this one: &lt;ENAMEX TYPE=\"PERSON\"&gt;Jim&lt;/ENAMEX&gt; bought &lt;NUMEX TYPE=\"QUANTITY\"&gt;300&lt;/NUMEX&gt; shares of &lt;ENAMEX TYPE=\"ORGANIZATION\"&gt;Acme Corp. &lt;/ENAMEX&gt; in &lt;TIMEX TYPE=\"DATE\"&gt;2006&lt;/TIMEX&gt;. In this example, the annotations have been done using so-called ENAMEX tags that were developed for the Message Understanding Conference in the 1990s. State-of-the-art NER systems produce near-human performance. For example, the best system entering MUC-7 scored 93.39% of f-measure while human annotators scored 97.60% and 96.95%. These results indicate the algorithms had roughly twice the error rate (6.61%) as human annotators (2.40% and 3.05%)."@en ,
		"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. Desde 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 ,
		"La reconnaissance d'entit\u00E9s nomm\u00E9es est une sous-t\u00E2che de l'activit\u00E9 d'extraction d'information dans des corpus documentaires. Elle consiste \u00E0 rechercher des objets textuels (c'est-\u00E0-dire un mot, ou un groupe de mot) cat\u00E9gorisables dans des classes telles que noms de personnes, noms d'organisations ou d'entreprises, noms de lieux, quantit\u00E9s, distances, valeurs, dates, etc."@fr ;
	rdfs:comment	"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 ,
		"\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\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 (NER) (also known as entity identification 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. Most research on NER systems has been structured as taking an unannotated block of text, such as this one: Jim bought 300 shares of Acme Corp. in 2006."@en ,
		"La reconnaissance d'entit\u00E9s nomm\u00E9es est une sous-t\u00E2che de l'activit\u00E9 d'extraction d'information dans des corpus documentaires. Elle consiste \u00E0 rechercher des objets textuels (c'est-\u00E0-dire un mot, ou un groupe de mot) cat\u00E9gorisables dans des classes telles que noms de personnes, noms d'organisations ou d'entreprises, noms de lieux, quantit\u00E9s, distances, valeurs, dates, etc."@fr .
@prefix skos:	<http://www.w3.org/2004/02/skos/core#> .
@prefix ns8:	<http://dbpedia.org/resource/Category:> .
dbpedia:Named_entity_recognition	skos:subject	ns8:Computational_linguistics ,
		ns8:Tasks_of_Natural_language_processing .
@prefix ns9:	<http://www4.wiwiss.fu-berlin.de/flickrwrappr/photos/> .
dbpedia:Named_entity_recognition	dbpprop:hasPhotoCollection	ns9:Named_entity_recognition .
<http://dbpedia.org/resource/Recognition_%28disambiguation%29>	dbpprop:disambiguates	dbpedia:Named_entity_recognition .
dbpedia:Named_Entity_Recognition	dbpprop:redirect	dbpedia:Named_entity_recognition .
dbpedia:Named_entity	dbpprop:redirect	dbpedia:Named_entity_recognition .
dbpedia:Named-entity_recognition	dbpprop:redirect	dbpedia:Named_entity_recognition .
dbpedia:ENAMEX	dbpprop:redirect	dbpedia:Named_entity_recognition .
dbpedia:Entity_extraction	dbpprop:redirect	dbpedia:Named_entity_recognition .
@prefix ns10:	<http://dbpedia.org/resource/Data_mining/> .
ns10:columns-list4	dbpprop:columnsListProperty	dbpedia:Named_entity_recognition .
dbpedia:Named-entity_detection	dbpprop:redirect	dbpedia:Named_entity_recognition .