{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-template-independent-approach-for","title":"A template-independent approach for information extraction in real estate documents","arxiv_id":null,"date":"2023-05-30","proceeding":"Ital-IA 2023 5","authors":["Nicola Landro","Gabriele Destro","Stefano Taverni","Ignazio Gallo"],"abstract":"Business corporations manage tons of unstructured data daily, such as PDFs and websites. Recent advances in the deep\r\nlearning field help find insight from this unstructured information. New models leverage the power of the Transformer\r\narchitecture to accomplish natural language understanding tasks on these data, jointly using the raw image and its text\r\ncontent or directly the image without OCR. We propose an extraction pipeline that employs question-answering models\r\nto get insight from unstructured data, allowing fast and efficient information retrieval from different sources. We show an\r\napplication of this technique to a specific set of documents and how we can scale this infrastructure to different types of\r\nrecords. Our solution can effectively handle large document corpora robustly, helping corporations exploit all the power\r\ncoming from their data.","url_abs":"https://www.ital-ia2023.it/workshop/ai-per-la-finanza-ed-il-commercio","url_pdf":"https://www.ital-ia2023.it/submission/17/paper","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-template-independent-approach-for","repo_url":"https://github.com/MrFeelgoood/RealEstateStocksForecasting","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"information-retrieval","task_name":"Information Retrieval"},{"task_slug":"natural-language-understanding","task_name":"Natural Language Understanding"},{"task_slug":"optical-character-recognition","task_name":"Optical Character Recognition (OCR)"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}