{"id":8042,"date":"2026-09-30T10:00:00","date_gmt":"2026-09-30T10:00:00","guid":{"rendered":"https:\/\/dev95.site\/stop-choosing-tools-start-building-them\/"},"modified":"2026-09-30T10:00:00","modified_gmt":"2026-09-30T10:00:00","slug":"stop-choosing-tools-start-building-them","status":"publish","type":"post","link":"https:\/\/dev95.site\/ar\/stop-choosing-tools-start-building-them\/","title":{"rendered":"Stop Choosing Tools. Start Building Them."},"content":{"rendered":"<div id=\"dev95-2846111665\" class=\"dev95-- dev95-entity-placement\"><script async=\"async\" data-cfasync=\"false\" src=\"https:\/\/pl27862732.profitableratecpmnetwork.com\/2ad7a50e0bbc23ac6801d7b77c501463\/invoke.js\"><\/script>\r\n<div id=\"container-2ad7a50e0bbc23ac6801d7b77c501463\"><\/div><\/div><div id=\"dev95-405602205\" class=\"dev95-before-content dev95-entity-placement\"><p style=\"text-align: center;\"><strong>Stop wasting time on dead links! \ud83d\uded1 This smart platform automatically detects your device and country to give you the exact best offer instantly. Check it out now 100% free! \ud83d\udc47<\/strong><br data-sfc-root=\"ep\" data-sfc-pl=\"|||[]\" data-complete=\"true\" data-copy-service-computed-style=\"font-family: Arial, sans-serif, &quot;Noto Color Emoji&quot;; font-size: 16px; font-weight: 400; margin: 0px; text-decoration: none; border-bottom: 0px rgb(10, 10, 10);\" \/><a href=\"https:\/\/www.profitableratecpmnetwork.com\/pvhx5mbcc?key=ff7d362db3c20bc86fad685cc94f1fc4\">\ud83d\udd17 <strong class=\"rQesXe MPyX\" data-sfc-cp=\"\" data-sfc-root=\"ep\" data-complete=\"true\" aria-owns=\"action-menu-parent-container\" data-copy-service-computed-style=\"font-family: Arial, sans-serif, &quot;Noto Color Emoji&quot;; font-size: 16px; font-weight: 700; margin: 0px; text-decoration: none; border-bottom: 0px rgb(10, 10, 10);\">[Click here]<\/strong><\/a><\/p>\n<\/div><div>\n<p class=\"wp-block-paragraph\"><em>Jacob Polay with Chlo\u00eb Farr and Jessica Jack<\/em><\/p><div id=\"dev95-2001069017\" class=\"dev95- dev95-entity-placement\"><center>\r\n<script>\r\n  atOptions = {\r\n    'key' : '4ba6b6513c00e0ba76511f798ae56401',\r\n    'format' : 'iframe',\r\n    'height' : 50,\r\n    'width' : 320,\r\n    'params' : {}\r\n  };\r\n<\/script>\r\n<script src=\"https:\/\/www.highrevenueformat.com\/4ba6b6513c00e0ba76511f798ae56401\/invoke.js\"><\/script>\r\n\t<\/center><\/div>\n<p class=\"wp-block-paragraph\"><em>This post is part of a <a href=\"https:\/\/activehistory.ca\/ai-and-collaboration\/\">series on AI and Collaboration.<\/a><\/em><\/p>\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img data-recalc-dims=\"1\" fetchpriority=\"high\" decoding=\"async\" width=\"832\" height=\"550\" data-attachment-id=\"144246\" data-permalink=\"https:\/\/activehistory.ca\/blog\/2026\/09\/30\/building-ai-tools-historical-research\/ah-ai-post-2\/\" data-orig-file=\"https:\/\/activehistory.ca\/wp-content\/uploads\/2026\/09\/AH-AI-Post.png\" data-orig-size=\"832,550\" data-comments-opened=\"1\" data-image-meta='{\"aperture\":\"0\",\"credit\":\"\",\"camera\":\"\",\"caption\":\"\",\"created_timestamp\":\"0\",\"copyright\":\"\",\"focal_length\":\"0\",\"iso\":\"0\",\"shutter_speed\":\"0\",\"title\":\"\",\"orientation\":\"0\",\"alt\":\"\"}' data-image-title=\"AH AI Post\" data-image-description=\"\" data-image-caption=\"\" data-large-file=\"https:\/\/activehistory.ca\/wp-content\/uploads\/2026\/09\/AH-AI-Post.png\" src=\"https:\/\/i0.wp.com\/activehistory.ca\/wp-content\/uploads\/2026\/09\/AH-AI-Post.png?resize=832%2C550&#038;ssl=1\" alt=\"\" class=\"wp-image-144246\" srcset=\"https:\/\/activehistory.ca\/wp-content\/uploads\/2026\/09\/AH-AI-Post.png 832w, https:\/\/activehistory.ca\/wp-content\/uploads\/2026\/09\/AH-AI-Post-300x198.png 300w, https:\/\/activehistory.ca\/wp-content\/uploads\/2026\/09\/AH-AI-Post-768x508.png 768w, https:\/\/activehistory.ca\/wp-content\/uploads\/2026\/09\/AH-AI-Post-624x413.png 624w\" sizes=\"(max-width: 832px) 100vw, 832px\"><\/figure>\n<\/div>\n<p class=\"has-text-align-center wp-block-paragraph\"><em>Archive boxes by Pexels. Free for use under the Pixabay content license.<\/em><\/p>\n<p class=\"wp-block-paragraph\">Transcribing archival documents is an important part of historical research, but a transcribed archive is still just prose. Before a historian can map trade routes and build databases to trace a merchant across ten thousand pages, they must turn this prose into useful data, identifying and tagging the persons, places, organizations, and other relevant entities within the text. Doing this by hand at a useful scale is impossible. Instead, historians most commonly turn to software called Named Entity Recognition (NER), which powers most of the structured historical data you\u2019ve ever queried, from tagged court records to place-name indexes.<\/p>\n<p class=\"wp-block-paragraph\">NER has evolved through three generations. The oldest systems were rules-based: using sophisticated, frequently hand-curated, gazetteers that matched text against lists and patterns. The second generation transformer models used the context of the sentence both before and after each word to distinguish that word\u2019s meaning. For example, these systems could separate \u201cTurkey\u201d the place from \u201cturkey\u201d the animal by identifying context clues, like reading \u201cIstanbul\u201d or \u201cfeather,\u201d in the sentence around the word. The newest generation uses large language models (LLMs), colloquially known as AI, which bring general linguistic knowledge to the task. This generalized knowledge allows these models to perform at a higher standard, providing more accurate results when identifying historical entities. Each generation improves on the last, but all share a limitation in that each model performs only as well as its training data resembles the documents under analysis, and almost nothing is trained using historical documents, especially ones as old as the early modern period.<\/p>\n<p class=\"wp-block-paragraph\">The consequences of this lack of historical training are significant. To measure NER performance, I ran one hundred pages of OCR\u2019d early modern text through fifteen systems and compared every tag against a <a href=\"https:\/\/doi.org\/10.5281\/zenodo.20420664\">hand-tagged gold standard<\/a> covering four entity types: people, places, commodities, and organizations. <a href=\"https:\/\/spacy.io\/usage\/spacy-101\">spaCy<\/a>, the free tool commonly used by humanists, missed most of what matters and scored just 20 percent on the standard accuracy measure. General LLMs like Google\u2019s Gemini 3 Pro performed better, reaching 67 percent, but its failures are telling. Gemini hallucinated over 450 false entities, manufacturing patterns that do not exist in the sources. Other typical errors included entities filed under the wrong type entirely, such as reading the \u201cEast-India Company\u201d as the place \u201cEast India.\u201d These errors are not random noise that washes out at scale; they\u2019re systemic, mis-tagging the same items the same way every time.<\/p>\n<p><span id=\"more-144099\"><\/span><\/p>\n<p class=\"wp-block-paragraph\">Part of the reason those systems created these kinds of errors was that they were not created for historical research. However, looking at these errors from a historian\u2019s lens allowed me to create a better solution for history. Additionally, I noticed that those systems had a tendency to repress those entities which appear only rarely in the corpus. Sometimes, the most valuable entities, the obscure people and the once-mentioned places, are the very heart of where historical discovery is found. Fixing the systemic problems, and surfacing these obscure entities, were my goals in creating my own solution.<\/p>\n<p class=\"wp-block-paragraph\">Through testing, the evident solution wasn\u2019t to find a better product. It was building one. Over a few weeks working with an LLM coding assistant, I fine-tuned a <a href=\"https:\/\/huggingface.co\/Qwen\/Qwen3-4B\">small open-source model<\/a> on training data I curated by hand, producing <a href=\"https:\/\/github.com\/polayj\/earlymodernner\">EarlyModernNER<\/a>. This model, which was trained on a home computer using consumer grade hardware, scored 82 percent, roughly 10 percent higher than Gemini 3 Pro, while filing zero entities under the wrong type, which no other model could do. It runs on most computers and is free to access via Github. More importantly, it is completely open and retrainable, meaning any historian with their own hand-tagged sample of sources can take the model and teach it their period\u2019s documents.<\/p>\n<p class=\"wp-block-paragraph\">The exact numbers achieved by EarlyModernNER matter less than the decisions behind them. Every design choice was a historical judgment: privileging precision over recall, because a hallucinated entry is worse than a missed mention; selecting entity categories that reflect what my historical investigation required; curating training data as an act of source criticism.\u00a0<\/p>\n<p class=\"wp-block-paragraph\">For decades, humanists have been consumers of models built by and for other fields, applying them to our studies with little modification. With the emergence of LLM coding assistants like Anthropic\u2019s Claude, small but mighty open-weight models, and consumer hardware becoming more powerful, the creation of digital tools for historians\u2014once the function of the all too rare funded lab\u2014is now within reach of a single researcher. Off-the-shelf tools may fail to produce useful data with your sources, but that\u2019s no longer the end of the story. It\u2019s the starting point. Historians now have the power to create our own tools, which can be shared with one another to empower the research of the entire field. Every gold standard, every shared dataset, every time a historian publishes open code to GitHub raises the floor for the next researcher, allowing our computational labour to compound on itself the way our research always has with footnotes. Now is the time to build. But even more, now is the time to collaborate.<\/p>\n<p class=\"wp-block-paragraph\"><em><strong>Jacob Polay<\/strong>\u00a0is a PhD student in History at the University of Saskatchewan, studying the roles Large Language Models have in the historical method. His current research involves creating an information retrieval pipeline using artificial intelligence tools to unlock the early modern archive at scale.<\/em><\/p>\n<p class=\"wp-block-paragraph\"><strong><em>Chlo\u00eb Farr<\/em><\/strong><em>\u00a0is a researcher working at the intersection of artificial intelligence, archives, and digital humanities.<\/em> <em>Working out of the Open Science Lab at TIB \u2013 Leibniz Information Centre for Science and Technology, her<\/em> <em>research focuses on large-scale text recognition and analysis of historical documents, including newspapers, maps, and archival records. Learn more about Farr\u2019s work on<\/em> <a href=\"https:\/\/chloe-farr.github.io\/\"><em>GitHub<\/em><\/a><em>.<\/em><\/p>\n<p class=\"wp-block-paragraph\"><em><strong>Jessica Jack<\/strong>\u00a0is a PhD student in History at the University of Saskatchewan, developing applications for Large Language Models in historical research. They are doing so through studying settler land use in late 19th century and early 20th century Saskatchewan.<\/em><\/p>\n<\/div>\n<div class=\"pvc_clear\"><\/div>\n<p id=\"pvc_stats_8042\" class=\"pvc_stats total_only  \" data-element-id=\"8042\" style=\"\"><i class=\"pvc-stats-icon large\" aria-hidden=\"true\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"far\" data-icon=\"chart-bar\" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\" class=\"svg-inline--fa fa-chart-bar fa-w-16 fa-2x\"><path fill=\"currentColor\" d=\"M396.8 352h22.4c6.4 0 12.8-6.4 12.8-12.8V108.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v230.4c0 6.4 6.4 12.8 12.8 12.8zm-192 0h22.4c6.4 0 12.8-6.4 12.8-12.8V140.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v198.4c0 6.4 6.4 12.8 12.8 12.8zm96 0h22.4c6.4 0 12.8-6.4 12.8-12.8V204.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v134.4c0 6.4 6.4 12.8 12.8 12.8zM496 400H48V80c0-8.84-7.16-16-16-16H16C7.16 64 0 71.16 0 80v336c0 17.67 14.33 32 32 32h464c8.84 0 16-7.16 16-16v-16c0-8.84-7.16-16-16-16zm-387.2-48h22.4c6.4 0 12.8-6.4 12.8-12.8v-70.4c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v70.4c0 6.4 6.4 12.8 12.8 12.8z\" class=\"\"><\/path><\/svg><\/i> <img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" width=\"16\" height=\"16\" alt=\"Loading\" src=\"https:\/\/i0.wp.com\/dev95.site\/wp-content\/plugins\/page-views-count\/ajax-loader-2x.gif?resize=16%2C16&#038;ssl=1\" border=0 \/><\/p>\n<div class=\"pvc_clear\"><\/div>\n<div id=\"dev95-3114156467\" class=\"dev95-after-content dev95-entity-placement\"><p style=\"text-align: center;\"><strong>Finally, a link that actually works for your region and device! \ud83c\udf0d Get instant access to the top exclusive offers tailored just for you right now. Don&#8217;t miss out, click here! \ud83d\udc47<\/strong><br data-sfc-root=\"ep\" data-sfc-pl=\"|||[]\" data-complete=\"true\" data-copy-service-computed-style=\"font-family: Arial, sans-serif, &quot;Noto Color Emoji&quot;; font-size: 16px; font-weight: 400; margin: 0px; text-decoration: none; border-bottom: 0px rgb(10, 10, 10);\" \/><a href=\"https:\/\/www.profitableratecpmnetwork.com\/uzeja8ahze?key=bc876be53d6ad0ff6370ab8ea030e479\"><strong>\ud83d\udd17 [Click here]<\/strong><\/a><\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Jacob Polay with Chlo\u00eb Farr and Jessica Jack This post is part of a series on AI and Collaboration. Archive boxes by Pexels. Free for use under the Pixabay content license. Transcribing archival documents is an important part of historical<\/p>\n<div class=\"hosteria-entry-more\"><a href=\"https:\/\/dev95.site\/ar\/stop-choosing-tools-start-building-them\/\" class=\"no-underline font-light  group-hover:text-primary-800 dark:group-hover:text-primary-300 py-1\">Read more &gt;&gt;&gt;<\/a><\/div>\n<div class=\"pvc_clear\"><\/div>\n<p id=\"pvc_stats_8042\" class=\"pvc_stats total_only\" data-element-id=\"8042\" style=\"\"><i class=\"pvc-stats-icon large\" aria-hidden=\"true\"><svg aria-hidden=\"true\" focusable=\"false\" data-prefix=\"far\" data-icon=\"chart-bar\" role=\"img\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 512 512\" class=\"svg-inline--fa fa-chart-bar fa-w-16 fa-2x\"><path fill=\"currentColor\" d=\"M396.8 352h22.4c6.4 0 12.8-6.4 12.8-12.8V108.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v230.4c0 6.4 6.4 12.8 12.8 12.8zm-192 0h22.4c6.4 0 12.8-6.4 12.8-12.8V140.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v198.4c0 6.4 6.4 12.8 12.8 12.8zm96 0h22.4c6.4 0 12.8-6.4 12.8-12.8V204.8c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v134.4c0 6.4 6.4 12.8 12.8 12.8zM496 400H48V80c0-8.84-7.16-16-16-16H16C7.16 64 0 71.16 0 80v336c0 17.67 14.33 32 32 32h464c8.84 0 16-7.16 16-16v-16c0-8.84-7.16-16-16-16zm-387.2-48h22.4c6.4 0 12.8-6.4 12.8-12.8v-70.4c0-6.4-6.4-12.8-12.8-12.8h-22.4c-6.4 0-12.8 6.4-12.8 12.8v70.4c0 6.4 6.4 12.8 12.8 12.8z\" class=\"\"><\/path><\/svg><\/i> <img loading=\"lazy\" decoding=\"async\" width=\"16\" height=\"16\" alt=\"Loading\" src=\"https:\/\/dev95.site\/wp-content\/plugins\/page-views-count\/ajax-loader-2x.gif\" border=\"0\" \/><\/p>\n<div class=\"pvc_clear\"><\/div>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"fp_fajr_begins":"","fp_fajr_iqamah":"","fp_dhuhr_begins":"","fp_dhuhr_iqamah":"","fp_asr_begins":"","fp_asr_iqamah":"","fp_maghrib_begins":"","fp_maghrib_iqamah":"","fp_isha_begins":"","fp_isha_iqamah":"","fp_midnight":"","fp_midnight_name":"","fp_sunrise":"","fp_single_prayer_begins_title":"","fp_single_prayer_iqamah_title":"","fp_prayer_times_for_today":"","fp_hijra_date":"","fp_fajr_name":"","fp_dhuhr_name":"","fp_asr_name":"","fp_maghrib_name":"","fp_isha_name":"","fp_sunrise_name":"","fp_currentDate":"","fp_current_time":"","fp_current_title":"","fp_current_location":"","fp_masjid_name":"","fp_prayer_title":"","fp_next_prayer_iqamah_time":"","fp_next_prayer_iqamah_title":"","fp_next_prayer_begins_time":"","fp_next_prayer_begins_title":"","fp_next_prayer_title":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[37],"tags":[],"class_list":["post-8042","post","type-post","status-publish","format-standard","hentry","category-posts"],"a3_pvc":{"activated":true,"total_views":0,"today_views":0},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Stop Choosing Tools. Start Building Them. - Dev95<\/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:\/\/dev95.site\/ar\/stop-choosing-tools-start-building-them\/\" \/>\n<meta property=\"og:locale\" content=\"ar_AR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Stop Choosing Tools. Start Building Them. - Dev95\" \/>\n<meta property=\"og:description\" content=\"Jacob Polay with Chlo\u00eb Farr and Jessica Jack This post is part of a series on AI and Collaboration. Archive boxes by Pexels. Free for use under the Pixabay content license. 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