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    <abstract>Public procurement data is legally open, yet practically locked inside thousands of unstructured PDFs and inconsistent portal metadata. pAtChWoRK starts with these fragmented, unstructured sources then leverages a hybrid pipeline (traditional NLP with LLM-based technologies) to restructure this information into a navigable knowledge base. Specifically, pAtChWoRK corrects manual classification errors, extracts complex unstructured fields such as award and solvency criteria and tenders’ objectives, and assists users in easily navigating the tender landscape. This unified process enables more effective handling of the transparency bottlenecks that hinder competition and oversight in public administration. A user study with practitioners across different procurement</abstract>
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%0 Conference Proceedings
%T pAtChWoRK: Patching the Pieces of Public Procurement Documents
%A Calvo-Bartolomé, Lorena
%A Fortes, Saúl Blanco
%A Cedeño, Erick
%A Arenas-García, Jerónimo
%Y Durrett, Greg
%Y Jian, Ping
%S Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-392-0
%F calvo-bartolome-etal-2026-patchwork
%X Public procurement data is legally open, yet practically locked inside thousands of unstructured PDFs and inconsistent portal metadata. pAtChWoRK starts with these fragmented, unstructured sources then leverages a hybrid pipeline (traditional NLP with LLM-based technologies) to restructure this information into a navigable knowledge base. Specifically, pAtChWoRK corrects manual classification errors, extracts complex unstructured fields such as award and solvency criteria and tenders’ objectives, and assists users in easily navigating the tender landscape. This unified process enables more effective handling of the transparency bottlenecks that hinder competition and oversight in public administration. A user study with practitioners across different procurement
%U https://aclanthology.org/2026.acl-demo.55/
%P 556-565

Markdown (Informal)

[pAtChWoRK: Patching the Pieces of Public Procurement Documents](https://aclanthology.org/2026.acl-demo.55/) (Calvo-Bartolomé et al., ACL 2026)

• pAtChWoRK: Patching the Pieces of Public Procurement Documents (Calvo-Bartolomé et al., ACL 2026)

ACL

• Lorena Calvo-Bartolomé, Saúl Blanco Fortes, Erick Cedeño, and Jerónimo Arenas-García. 2026. pAtChWoRK: Patching the Pieces of Public Procurement Documents. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 556–565, San Diego, California, United States. Association for Computational Linguistics.