A well structured collection of the various Quantum Cascade Laser (QCL) design and working properties data provides a platform to analyze and understand the relationships between these properties. By analyzing these relationships, we can gain insights into how different design features impact laser performance properties such as the working temperature. Most of these QCL properties are captured in scientific text. There is therefore need for efficient methodologies that can be utilized to extract QCL properties from text and generate a semantically enriched and interlinked platform where the properties can be analyzed to uncover hidden relations. There is also the need to maintain provenance and reference information on which these properties are based. Semantic Web technologies such as Ontologies and Knowledge Graphs have proven capability in providing interlinked data platforms for knowledge representation in various domains. In this paper, we propose an approach for generating a QCL properties Knowledge Graph (KG) from text for semantic enrichment of the properties. The approach is based on the QCL ontology and a Retrieval Augmented Generation (RAG) enabled information extraction pipeline based on GPT 4-Turbo language model. The properties of interest include: working temperature, laser design type, lasing frequency, laser optical power and the heterostructure. The experimental results demonstrate the feasibility and effectiveness of this approach for efficiently extracting QCL properties from unstructured text and generating a QCL properties Knowledge Graph, which has potential applications in semantic enrichment and analysis of QCL data.

翻译：结构良好的量子级联激光器（QCL）设计与工作特性数据集合为分析和理解这些特性之间的关系提供了平台。通过分析这些关系，我们可以深入理解不同设计特征如何影响激光性能特性（如工作温度）。这些QCL特性大多记录在科学文本中。因此，需要高效的方法从文本中提取QCL特性，并生成语义增强且相互关联的平台，以便通过特性分析揭示隐藏关系。同时，还需要维护这些特性所依据的来源与参考文献信息。语义网技术（如本体和知识图谱）已在多个领域证明其能够为知识表示提供互联数据平台。本文提出一种从文本生成QCL特性知识图谱（KG）以实现特性语义增强的方法。该方法基于QCL本体和基于GPT-4 Turbo语言模型的检索增强生成（RAG）信息抽取流程。关注的特性包括：工作温度、激光设计类型、激射频率、激光光功率以及异质结构。实验结果证明了该方法从非结构化文本中高效提取QCL特性并生成QCL特性知识图谱的可行性与有效性，该图谱在QCL数据的语义增强与分析方面具有潜在应用价值。