Explainable Large Language Model for Islamic and Humanities Sciences Based on Knowledge Graphs

In recent decades, significant advancements have occurred in the fields of Islamic and human sciences. These advancements include the development of new technologies, innovative research methods, and improved understanding of complex concepts. However, considerable challenges remain in organizing and analyzing these concepts, particularly in the analysis of religious concepts and scientific inference. Despite the development of modern technologies such as knowledge graphs and large language models, the effective and synergistic application of these technologies in the realm of Islamic and human sciences has not yet been fully realized. One of the main reasons for this issue is the complexity and diversity of concepts and categories within these fields. Religious and human concepts inherently possess multiple dimensions and layers, requiring novel and efficient approaches for their analysis. Knowledge graphs are recognized as powerful tools for organizing information and displaying relationships between concepts. These tools can aid in clarifying and visualizing the intricate relationships among concepts, allowing researchers to easily understand the connections between various ideas. In contrast, large language models are capable of processing and comprehending natural language on a broad scale. These models can analyze texts and extract meaningful information from them, enabling researchers to quickly access the data they need. The combination of these two approaches can lead to the development of new frameworks for analyzing and inferring data in religious sciences, providing a suitable foundation for advanced research. This article proposes a model for integrating knowledge graphs and large language models, aiming to create a framework for more precise and efficient analysis of concepts in these fields. The goal of this model is to enhance the quality of analysis and inference in the domains of Islamic and human sciences, utilizing the aforementioned technologies. The research methodology of this study is based on a descriptive-analytical approach. This method, through library studies and conceptual analysis, identifies key concepts and existing structures. In this context, the hierarchical structures of concepts and conceptual inference have been organized in a manner that enables synergy between knowledge graphs and large language models. This facilitates improved processes of analysis and inference and allows for the development of more advanced systems. The proposed model of this research, based on linking scientific and religious concepts, enables automated responses and text generation. This framework can serve as a theoretical tool and can be applied in future research and the development of intelligent analytical systems. Moreover, utilizing this model can enhance efficiency and accuracy in analysis and inference across various fields of Islamic and human sciences. One notable feature of this model is its flexibility and adaptability to the diverse needs of researchers. This characteristic allows researchers to achieve deeper and more comprehensive analyses using this framework, contributing to a better understanding and more precise inference of religious and scientific concepts. Additionally, this model can serve as a foundation for developing educational and research tools within the field of Islamic and human sciences. Particularly in the realm of education, this framework can assist in developing innovative teaching and learning methods across various disciplines. Accurate analysis of religious and scientific concepts enables researchers to gain a better understanding of texts and sources, leading to new structures in human and religious knowledge. This is especially important in the context of social and cultural transformations that require a deeper understanding of religious and human concepts.

In conclusion, this research demonstrates that the integration of knowledge graphs and large language models can be proposed as an innovative and effective approach for analyzing and inferring complex concepts in Islamic and human sciences. It is hoped that this proposed framework can serve as a model for future research and the development of intelligent systems in these fields. This framework can act as a foundation for innovation and development in Islamic and human sciences, facilitating improvements in research and analysis processes. Ultimately, it is hoped that this study can lead to the development of new and effective methods for analyzing and inferring complex concepts in Islamic and human sciences and serve as a model for future research.