{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T11:38:15Z","timestamp":1778067495762,"version":"3.51.4"},"reference-count":66,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T00:00:00Z","timestamp":1745193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MAKE"],"abstract":"<jats:p>This paper introduces a novel framework enabling natural language question answering on Piping and Instrumentation Diagrams (P&amp;IDs), addressing a critical gap between engineering design documentation and intuitive information retrieval. Our approach transforms static P&amp;IDs into queryable knowledge bases through a three-stage pipeline. First, we recognize entities in a P&amp;ID image and organize their relationships to form a base entity graph. Second, this entity graph is converted into a Labeled Property Graph (LPG), enriched with semantic attributes for nodes and edges. Third, a Large Language Model (LLM)-based information retrieval system translates a user query into a graph query language (Cypher) and retrieves the answer by executing it on LPG. For our experiments, we augmented a publicly available P&amp;ID image dataset with our novel PIDQA dataset, which comprises 64,000 question\u2013answer pairs spanning four categories: (I) simple counting, (II) spatial counting, (III) spatial connections, and (IV) value-based questions. Our experiments (using gpt-3.5-turbo) demonstrate that grounding the LLM with dynamic few-shot sampling robustly elevates accuracy by 10.6\u201343.5% over schema contextualization alone, even under high lexical diversity conditions (e.g., paraphrasing, ambiguity). By reducing barriers in retrieving P&amp;ID data, this work advances human\u2013AI collaboration for industrial workflows in design validation and safety audits.<\/jats:p>","DOI":"10.3390\/make7020039","type":"journal-article","created":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T20:42:00Z","timestamp":1745268120000},"page":"39","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["PIDQA\u2014Question Answering on Piping and Instrumentation Diagrams"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0677-4811","authenticated-orcid":false,"given":"Mohit","family":"Gupta","sequence":"first","affiliation":[{"name":"School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287-1404, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8191-9091","authenticated-orcid":false,"given":"Chialing","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287-1404, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Czerniawski","sequence":"additional","affiliation":[{"name":"School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287-1404, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6904-5352","authenticated-orcid":false,"given":"Ricardo","family":"Eiris","sequence":"additional","affiliation":[{"name":"School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85287-1404, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1016\/S0268-4012(98)00032-2","article-title":"A Comparison Between the Provision of Information to Engineering Designers in the UK and the USA","volume":"18","author":"Court","year":"1998","journal-title":"Int. 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