A Semantic Annotation Pipeline towards the Generation of Knowledge Graphs in Tribology

Kügler P, Marian M, Dorsch R, Schleich B, Wartzack S (2022)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2022

Journal

Lubricants MDPI

Book Volume: 10

Article Number: 18

Journal Issue: 2

DOI: 10.3390/lubricants10020018

Open Access Link: https://www.mdpi.com/2075-4442/10/2/18

Abstract

Within the domain of tribology, enterprises and research institutions are constantly working on new concepts, materials, lubricants, or surface technologies for a wide range of applications. This is also reflected in the continuously growing number of publications, which in turn serve as guidance and benchmark for researchers and developers. However, those are almost impossible to keep up with due to their vast quantity and the associated complexity and diversity. Due to the lack of suited data and knowledge bases, knowledge acquisition and aggregation is still a manual process involving the time-consuming review of literature. Therefore, semantic annotation and natural language processing (NLP) techniques can decrease this manual effort by providing a semi-automatic support in knowledge acquisition. The generation of knowledge graphs from textual sources promises improved reuse and retrieval of information acquired from scientific literature in a structured way. Motivated by this, the contribution introduces a novel semantic annotation pipeline for generating knowledge graphs and streamline knowledge acquisition in the domain of tribology. The pipeline is built on BERT, a state-of-the-art language model and involves classic NLP tasks like information extraction, named entity recognition and question answering.

Authors with CRIS profile

Patricia Kügler Chair of Engineering Design Benjamin Schleich Chair of Engineering Design Sandro Wartzack Chair of Engineering Design

Related research project(s)

COFFEE - Collaborative Forgetting for Engineering Design SPP 1921: Intentional Forgetting in Organisationen.Mechanismen des Vergessens als Anpassungsleistungen von Organisationen an eine Umweltstetig wachsender Informationsmengen Jan. 1, 2020 - Dec. 31, 2022

Involved external institutions

Pontificia Universidad Católica de Chile CL Chile (CL)

How to cite

APA:

Kügler, P., Marian, M., Dorsch, R., Schleich, B., & Wartzack, S. (2022). A Semantic Annotation Pipeline towards the Generation of Knowledge Graphs in Tribology. Lubricants, 10(2). https://doi.org/10.3390/lubricants10020018

MLA:

Kügler, Patricia, et al. "A Semantic Annotation Pipeline towards the Generation of Knowledge Graphs in Tribology." Lubricants 10.2 (2022).

BibTeX: Download