{"id":6378,"date":"2025-08-27T07:02:25","date_gmt":"2025-08-27T07:02:25","guid":{"rendered":"https:\/\/mailitics.com\/index.php\/2025\/08\/27\/using-googles-langextract-and-gemma-for-structured-data-extraction\/"},"modified":"2025-08-27T07:02:25","modified_gmt":"2025-08-27T07:02:25","slug":"using-googles-langextract-and-gemma-for-structured-data-extraction","status":"publish","type":"post","link":"https:\/\/mailitics.com\/index.php\/2025\/08\/27\/using-googles-langextract-and-gemma-for-structured-data-extraction\/","title":{"rendered":"Using Google\u2019s LangExtract and Gemma for Structured Data Extraction"},"content":{"rendered":"<p>    Using Google\u2019s LangExtract and Gemma for Structured Data Extraction<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n    <!-- no image --><br \/>\n \t<BR><br \/>\n<BR><\/BR><\/p>\n<div>\n<p>Extracting structured information effectively and accurately from long unstructured text with LangExtract and\u00a0LLMs<\/p>\n<p>The post <a href=\"https:\/\/towardsdatascience.com\/using-googles-langextract-and-gemma-for-structured-data-extraction\/\">Using Google\u2019s LangExtract and Gemma for Structured Data Extraction<\/a> appeared first on <a href=\"https:\/\/towardsdatascience.com\/\">Towards Data Science<\/a>.<\/p>\n<\/div>\n<p> \t<BR><br \/>\n <BR><\/BR><br \/>\n    Kenneth Leung<br \/>\n \t<BR><br \/>\n<BR><\/BR><br \/>\n<a href=\"https:\/\/towardsdatascience.com\/using-googles-langextract-and-gemma-for-structured-data-extraction\/\">Go to original source<\/a><br \/>\n \t<BR><br \/>\n <BR><\/BR><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Using Google\u2019s LangExtract and Gemma for Structured Data Extraction Extracting structured information effectively and accurately from long unstructured text with LangExtract and\u00a0LLMs The post Using Google\u2019s LangExtract and Gemma for Structured Data Extraction appeared first on Towards Data Science. Kenneth Leung Go to original source<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[62,3603,83,71,87,70,3534],"tags":[84,3488,345],"class_list":["post-6378","post","type-post","status-publish","format-standard","hentry","category-aimldsaimlds","category-data-extraction","category-data-science","category-large-language-models","category-llm","category-machine-learning","category-structured-data","tag-data","tag-langextract","tag-structured"],"_links":{"self":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6378"}],"collection":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/comments?post=6378"}],"version-history":[{"count":0,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/posts\/6378\/revisions"}],"wp:attachment":[{"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/media?parent=6378"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/categories?post=6378"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mailitics.com\/index.php\/wp-json\/wp\/v2\/tags?post=6378"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}