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Leveraging large language models for automated knowledge graphs generation in non-destructive testing
- This paper presents an innovative approach for the automatic generation of Knowledge Graphs (KGs) from heterogeneous scientific articles in the domain of Non-Destructive Testing (NDT) applied to building materials.
Our methodology leverages large language models (LLMs) to extract and semantically relate concepts from diverse sources. We developed material-specific agents for concrete, wood, steel, and bricks, each equipped with a curated glossary of terms to ensure domain accuracy. These agents process PDF documents, extracting relevant information on deterioration mechanisms, physical changes, and applicable NDT methods. The extracted data is then normalized, validated, and structured into a Neo4j graph database, forming a comprehensive KG. Our results demonstrate the system’s ability to automatically discover and represent intricate relationships between materials, deterioration mechanisms, physical changes, and NDT techniques. The generated KG successfully captures complexThis paper presents an innovative approach for the automatic generation of Knowledge Graphs (KGs) from heterogeneous scientific articles in the domain of Non-Destructive Testing (NDT) applied to building materials.
Our methodology leverages large language models (LLMs) to extract and semantically relate concepts from diverse sources. We developed material-specific agents for concrete, wood, steel, and bricks, each equipped with a curated glossary of terms to ensure domain accuracy. These agents process PDF documents, extracting relevant information on deterioration mechanisms, physical changes, and applicable NDT methods. The extracted data is then normalized, validated, and structured into a Neo4j graph database, forming a comprehensive KG. Our results demonstrate the system’s ability to automatically discover and represent intricate relationships between materials, deterioration mechanisms, physical changes, and NDT techniques. The generated KG successfully captures complex interactions, such as the applicability of specific NDT methods to various materials under different deterioration conditions. This work not only highlights the potential of KGs in enhancing knowledge discovery and representation in NDT research but also provides a scalable framework for extending this approach to other scientific domains.…


| Autor*innen: | Ghezal Ahmad Jan ZiaORCiD, Andre ValdestilhasORCiD, Benjami Moreno TorresORCiD, Sabine KruschwitzORCiD |
|---|---|
| Dokumenttyp: | Beitrag zu einem Tagungsband |
| Veröffentlichungsform: | Graue Literatur |
| Sprache: | Englisch |
| Titel des übergeordneten Werkes (Englisch): | SeMatS 2024 - Proceedings of the first international workshop on semantic materials science: Harnessing the power of semantic web technologies in materials science |
| Jahr der Erstveröffentlichung: | 2024 |
| Organisationseinheit der BAM: | 8 Zerstörungsfreie Prüfung |
| 8 Zerstörungsfreie Prüfung / 8.0 Abteilungsleitung und andere | |
| Veröffentlichende Institution: | Bundesanstalt für Materialforschung und -prüfung (BAM) |
| Verlag: | RWTH Aachen |
| Verlagsort: | Aachen |
| Jahrgang/Band: | 3760 |
| Aufsatznummer: | 11 |
| Erste Seite: | 101 |
| Letzte Seite: | 110 |
| DDC-Klassifikation: | Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurwissenschaften und zugeordnete Tätigkeiten |
| Freie Schlagwörter: | Data interoperability; Large language model; Linked open data; Materials science and engineering; RDF; Semantic web |
| Themenfelder/Aktivitätsfelder der BAM: | Material |
| Material / Materialdesign | |
| Veranstaltung: | SeMatS 2024 - The 1st International Workshop on Semantic Materials Science |
| Veranstaltungsort: | Amsterdam, The Netherlands |
| Beginndatum der Veranstaltung: | 17.09.2024 |
| DOI: | 10.5281/zenodo.13834164 |
| URN: | urn:nbn:de:kobv:b43-624597 |
| ISSN: | 1613-0073 |
| Zugehöriger Identifikator: | https://opus4.kobv.de/opus4-bam/frontdoor/index/index/docId/62497 |
| Bemerkung: | Serientitel: CEUR workshop proceedings – Series title: CEUR workshop proceedings |
| Verfügbarkeit des Dokuments: | Datei für die Öffentlichkeit verfügbar ("Open Access") |
| Lizenz (Deutsch): | Creative Commons - CC BY - Namensnennung 4.0 International |
| Datum der Freischaltung: | 04.02.2025 |
| Referierte Publikation: | Nein |
| Schriftenreihen ohne Nummerierung: | Wissenschaftliche Artikel der BAM |


