{"id":171274,"date":"2014-01-29T05:13:21","date_gmt":"2014-01-29T05:13:21","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/project\/named-entity-recognizer-ner\/"},"modified":"2016-07-17T09:13:47","modified_gmt":"2016-07-17T16:13:47","slug":"named-entity-recognizer-ner","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/named-entity-recognizer-ner\/","title":{"rendered":"Named Entity Recognizer (NER)"},"content":{"rendered":"<h2 class=\"asset-content\">Definition<\/h2>\n<div id=\"en-usprojectsnerdefault\" class=\"page-content\">\n<p>Detects and classifies named entities for persons, locations and organizations categories<\/p>\n<h2>Features<\/h2>\n<h3>Arabic named entities detection and classification<\/h3>\n<p>The Arabic Named Entity Recognizer (NER) extracts named entities from standard Arabic text and classifies them into three main types: proper names, locations, and organizations. Arabic NER can extract foreign and Arabic names, location entities such as cities, countries, streets, squares, as well as organizations like sports teams, political parties, companies, and ministries.<\/p>\n<h3>Arabic text preprocessing<\/h3>\n<p>Arabic NER uses the Speller to correct spelling mistakes during preprocessing. The user has the option to select between having spell checking or automatic correction, depending on the error rate of the input text. Automatic correction is recommended for text with a low error rate, while spell checking is preferred for text with a high error rate.<\/p>\n<h2>API<\/h2>\n<ul>\n<li><strong>Get Named Entities<\/strong> detects and classifies named entities in the input text<\/li>\n<\/ul>\n<h2>Example<\/h2>\n<table>\n<tbody>\n<tr>\n<td style=\"vertical-align: middle;\"><span id=\"42ef8e06-14cc-4b29-8f13-babe895ba36d\" class=\"ImageBlock fn\"><img decoding=\"async\" id=\"Image42ef8e06-14cc-4b29-8f13-babe895ba36d\" class=\"aligncenter\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/atks-ner-example1.png\" alt=\"\" \/><span id=\"ImageCaption42ef8e06-14cc-4b29-8f13-babe895ba36d\" class=\"ImageCaptionCoreCss ImageCaption\"><\/span><\/span><\/td>\n<td><span id=\"d351d3b9-0f82-4710-b783-b7811af816e5\" class=\"ImageBlock fn\"><img decoding=\"async\" id=\"Imaged351d3b9-0f82-4710-b783-b7811af816e5\" class=\"aligncenter\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/atks-ner-example2.png\" alt=\"\" \/><span id=\"ImageCaptiond351d3b9-0f82-4710-b783-b7811af816e5\" class=\"ImageCaptionCoreCss ImageCaption\"><\/span><\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><a href=\"https:\/\/www.microsoft.com\/en-us\/research\/project\/arabic-toolkit-service-atks\/\">back to ATKS<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Definition Detects and classifies named entities for persons, locations and organizations categories Features Arabic named entities detection and classification The Arabic Named Entity Recognizer (NER) extracts named entities from standard Arabic text and classifies them into three main types: proper names, locations, and organizations. Arabic NER can extract foreign and Arabic names, location entities such [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13545],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-171274","msr-project","type-msr-project","status-publish","hentry","msr-research-area-human-language-technologies","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"2014-01-29","related-publications":[],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[],"msr_research_lab":[],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171274","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171274\/revisions"}],"predecessor-version":[{"id":213946,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171274\/revisions\/213946"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=171274"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=171274"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=171274"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=171274"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=171274"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}