{"id":765491,"date":"2020-03-10T10:34:35","date_gmt":"2020-03-10T17:34:35","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=765491"},"modified":"2020-03-13T10:23:32","modified_gmt":"2020-03-13T17:23:32","slug":"dev-summit-2020-extract-and-map-data-from-unstructured-text-2","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/api-python\/analytics\/dev-summit-2020-extract-and-map-data-from-unstructured-text-2","title":{"rendered":"Dev Summit 2020: Extract and map data from unstructured text"},"author":6911,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,24371],"tags":[387782,174212,186132,30181,25631],"industry":[],"product":[36841,36571,36561],"class_list":["post-765491","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-public-safety","tag-arcgis-api-for-python","tag-artificial-intelligence","tag-deep-learning","tag-developer-summit","tag-spatial-analysis","product-api-python","product-arcgis-enterprise","product-arcgis-pro"],"acf":{"short_description":"Learn how you can use natural language processing and deep learning to extract and map information from unstructured text files.","flexible_content":[{"acf_fc_layout":"content","content":"<p>Geospatial data doesn&#8217;t always come neatly packaged in the form of file geodatabases and shapefiles. Often, data is hidden away in an unstructured format, such as text-based reports.<\/p>\n<p>To use this data with ArcGIS, you need to convert it into a structured, standardized format. However, it is difficult and time consuming to read and convert unstructured text.<\/p>\n"},{"acf_fc_layout":"content","content":"<p>At the Developer Summit 2020 plenary, Lauren Bennett demonstrated how you can automate this process using the <a href=\"https:\/\/developers.arcgis.com\/python\/api-reference\/arcgis.learn.html\">Learn module<\/a> of <a href=\"https:\/\/developers.arcgis.com\/python\/api-reference\/arcgis.learn.html\">ArcGIS API for Python<\/a>.<\/p>\n<p>She analyzed thousands of <span data-contrast=\"none\">unstructured text files containing<\/span> <span data-contrast=\"none\"><a href=\"https:\/\/www.cityofmadison.com\/police\/newsroom\/incidentreports\/\">police reports from Madison, Wisconsin<\/a>, <\/span>and created a map of the crime locations.<\/p>\n<p>You can watch the presentation below. Then read the rest of the blog for a summary of the information you need to implement the same type of workflow in your organization.<\/p>\n"},{"acf_fc_layout":"youtube","start_time":"0","end_time":"","youtube_video_url":"<iframe title=\"Natural Language Processing\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/LTG6iZnaYdg?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe>"},{"acf_fc_layout":"content","content":"<h1>Prepare training data<\/h1>\n<p>First, Lauren labeled the contents of a subset of text files to define important entities related to crime data. Entities in the presentation included the <span data-contrast=\"none\">location, time, and type of crime, time the crime was reported, reporting officer, and weapons used. <\/span><\/p>\n<p><span data-contrast=\"none\">An open source text annotation tool named <a href=\"https:\/\/github.com\/doccano\/doccano\">Doccano<\/a> was used to label the entities. <\/span><\/p>\n<p><span data-contrast=\"none\">These labeled text reports served as training data to train an AI model to extract these entities from unstructured text.\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":765481,"id":765481,"title":"Crime incident report with labelled entities","filename":"labelling.png","filesize":24599,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/labelling.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/api-python\/analytics\/dev-summit-2020-extract-and-map-data-from-unstructured-text\/labelling","alt":"Crime incident report labelled to show entities that should be extracted","author":"6911","description":"Crime incident report with labelled entities describing the type of crime, where it occurred, time of incident and reporting, etc. Doccano, an open source text annotation tool was used to label the entities in a small subset of the reports. ","caption":"Crime incident report with labelled entities, highlighting entities such as the type of crime, where it occurred, time of incident and when it was reported.","name":"labelling","status":"inherit","uploaded_to":753761,"date":"2020-03-10 11:41:59","modified":"2020-03-10 12:32:25","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1085,"height":516,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/labelling-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/labelling.png","medium-width":464,"medium-height":221,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/labelling.png","medium_large-width":768,"medium_large-height":365,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/labelling.png","large-width":1085,"large-height":516,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/labelling.png","1536x1536-width":1085,"1536x1536-height":516,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/labelling.png","2048x2048-width":1085,"2048x2048-height":516,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/labelling-826x393.png","card_image-width":826,"card_image-height":393,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/labelling.png","wide_image-width":1085,"wide_image-height":516}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h1>Train the model<\/h1>\n<p>Next, Lauren used the <a href=\"https:\/\/developers.arcgis.com\/python\/api-reference\/arcgis.learn.html\">arcgis.learn<\/a> module and the training data to train an EntityRecognizer model.<\/p>\n<p>Training such natural language processing models is just like training computer vision models using the <em>arcgis.learn<\/em> module.\u00a0You create the model, fit it to the training data, visualize results and save it for later use.<\/p>\n<p>Once satisfied that the model could identify the information they needed, Lauren used it to extract the entities from all the text files.<span data-contrast=\"none\"> This resulted in a pandas data frame containing the extracted entities for each police report.<\/span><\/p>\n"},{"acf_fc_layout":"content","content":"<h1>Create a feature layer<\/h1>\n<p>With the data in a structured data frame, she could use ArcGIS API for Python to geocode the locations and create a point feature layer. Each point represented a crime location.<\/p>\n<p>When added to a map, clicking a point showed the police report and the specific entities extracted for each crime.<\/p>\n<p>Additionally, the extracted crime was clustered into different categories using <a href=\"https:\/\/scikit-learn.org\/stable\/\">scikit-learn<\/a>, a popular machine learning library.<\/p>\n<p>You can <a href=\"https:\/\/arcg.is\/99m5v0\">view a web map containing the published feature layer<\/a>.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":765501,"id":765501,"title":"Extracted Crime Incidents","filename":"madison_crime.png","filesize":296569,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/madison_crime.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/api-python\/analytics\/dev-summit-2020-extract-and-map-data-from-unstructured-text-2\/madison_crime","alt":"Crime points","author":"6911","description":"Crime points created from extracted locations","caption":"Feature layer of crime incidents","name":"madison_crime","status":"inherit","uploaded_to":765491,"date":"2020-03-10 12:13:41","modified":"2020-03-10 12:31:11","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":803,"height":570,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/madison_crime-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/madison_crime.png","medium-width":368,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/madison_crime.png","medium_large-width":768,"medium_large-height":545,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/madison_crime.png","large-width":803,"large-height":570,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/madison_crime.png","1536x1536-width":803,"1536x1536-height":570,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/madison_crime.png","2048x2048-width":803,"2048x2048-height":570,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/madison_crime-655x465.png","card_image-width":655,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/madison_crime.png","wide_image-width":803,"wide_image-height":570}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<h1>Try it for yourself<\/h1>\n<p>Follow these links to additional resources to help you use the arcgis.learn module to extract and map data from unstructured text files:<\/p>\n<ul>\n<li><a href=\"https:\/\/developers.arcgis.com\/python\/guide\/how-named-entity-recognition-works\/\">Named Entity Extraction Workflow with arcgis.learn<\/a><\/li>\n<li><a href=\"https:\/\/developers.arcgis.com\/python\/sample-notebooks\/information-extraction-from-madison-city-crime-incident-reports-using-deep-learning\/\">Information extraction from crime incident reports using Deep Learning<\/a><\/li>\n<li><a href=\"https:\/\/developers.arcgis.com\/python\/guide\/\">ArcGIS API for Python guide<\/a><\/li>\n<\/ul>\n"}],"authors":[{"ID":6911,"user_firstname":"Rohit","user_lastname":"Singh","nickname":"Rohit Singh","user_nicename":"rsinghesri-com","display_name":"Rohit Singh","user_email":"rsingh@esri.com","user_url":"","user_registered":"2018-03-02 00:19:00","user_description":"Rohit Singh is Director of Esri\u2019s R&amp;D Center in New Delhi, leading the design and development of Geospatial AI capabilities across the ArcGIS platform. He has played a key role in the development of ArcGIS API for Python, ArcGIS Java Engine API, and the Linux enablement of ArcGIS. An alumnus of IIT Kharagpur, Rohit holds an MS in Computer Science with specialization in AI from Georgia Tech.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/08\/RohitSingh_AISummit2025-213x200.jpeg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"},{"ID":9882,"user_firstname":"Kim","user_lastname":"Peter","nickname":"Kim Peter","user_nicename":"kpeter","display_name":"Kimberly Peter","user_email":"kpeter@esri.com","user_url":"","user_registered":"2019-08-20 16:17:51","user_description":"I work with several product teams at Esri to test user experiences and translate developer-speak into customer-speak.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2019\/08\/JasperCA.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"}],"related_articles":[{"ID":764201,"post_author":"6181","post_date":"2020-03-10 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clouds","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"dev-summit-2020-use-ai-to-extract-data-from-lidar-point-clouds","to_ping":"","pinged":"","post_modified":"2020-03-13 10:16:55","post_modified_gmt":"2020-03-13 17:16:55","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=760941","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":764771,"post_author":"7351","post_date":"2020-03-10 12:06:22","post_date_gmt":"2020-03-10 19:06:22","post_content":"","post_title":"Dev Summit 2020: Automation comes to ArcGIS Notebooks","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"dev-summit-2020-automation-comes-to-arcgis-notebooks","to_ping":"","pinged":"","post_modified":"2020-03-16 14:18:18","post_modified_gmt":"2020-03-16 21:18:18","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=764771","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"5","filter":"raw"}],"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/IMG_2883card.jpg","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/IMG_2883banner.jpg"},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Dev Summit 2020: Extract and map data from unstructured text<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/api-python\/analytics\/dev-summit-2020-extract-and-map-data-from-unstructured-text-2\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta 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