Call for papers: Special Issue on

Large Language Models, Generative AI and Knowledge Graphs

The development and deployment of Large Language Models and Generative AI are having a major impact on the Semantic Web: recently, the 21st Extended Semantic Web Conference (ESWC 2024) and the 23rd International Semantic Web Conference (ISWC 2024) have featured Special Tracks on Large Language Models for Knowledge Engineering (https://2024.eswc-conferences.org/special-track-llms-for-ke/) and on Harmonising Generative AI and Semantic Web Technologies: Opportunities, challenges, and benchmarks (https://iswc2024.semanticweb.org/event/3715c6fc-e2d7-47eb-8c01-5fe4ac589...). An upcoming AAAI Fall Symposium will be specifically focused on Large Language Models for Knowledge Graphs and Ontology Engineering (https://kastle-lab.github.io/llms-and-kg-engineering/).

These events have shown that these models are transforming the ways in which we think about and approach various phases of knowledge graph development, such as requirements engineering, competency questions, ontology engineering, ontology and knowledge graph documentation, etc. At the same time, these models pose new questions and challenges around explainability, accountability and evaluation.

This special issue builds directly on top of the outcomes of these recent events. The scope of the present special issue is to provide an opportunity to develop and expand early results in the area of large language models, generative AI and knowledge graphs previously published in ESWC 2024 and ISWC 2024, as well as to welcome new research in this exciting new area.

Themes and Topics

We encourage the authors of papers presented at the Special Track on LLMs for KE in ESWC 2024 and the Special Session on LLMs at ISWC 2024 to submit extended versions of their papers (see the “Author Guidelines” section below for details). We also encourage the submission of novel, previously unpublished research related, but not limited, to one or more of the following themes and topics:

• Techniques for seamless integration and interoperability between KGs, LLMs, and other AI components
• Novel methodologies for integrating KGs, LLMs, and AI technologies in specific domains, such as natural language processing, information retrieval, decision support systems, etc.
• Evaluation of LLMs and Generative AI for Knowledge Engineering
• Benchmarks and reproducibility of LLMs/GenAI for Knowledge Engineering
• Evaluation of knowledge graph development tasks based on LLMs/GenAI
• Knowledge Graph-based retrieval augmented generation (RAG)
• Drafting of ontology classes and properties
• Knowledge base population and refinement
• Knowledge graph completion, including multiple modalities, with LLMs/GenAI
• Competency question generation and retrofitting
• Human in the loop activities
• Data quality and profiling in integrated LLM, GenAI and KG systems
• Knowledge base alignment
• Extraction of rich knowledge structures
• Generating and extending documentation for ontologies and knowledge graphs
• Conversational knowledge engineering
• Ontology and knowledge graph engineering methodologies based on LLMs/GenAI
• Ontology matching with LLMs/GenAI
• Guardrailing, safety and hallucination prevention in using LLMs/GenAI for knowledge graphs
• Using LLMs/GenAI in knowledge graph reasoning

Authors Guidelines

We invite full papers, dataset descriptions, benchmarks, and frameworks and systems. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this special issue. Authors can extend previously published conference or workshop papers; guidelines for this can be found in FAQ 9. In particular, we welcome submissions in the following three strands:

1. ESWC 2024: accepted papers for publication in: (a) the Research Track that used LLMs/GenAI as a principal component of the research; or (b) in the Special Track on LLMs for KE
2. ISWC 2024: white papers compiling the results and discussions of papers in the Special Session in LLMs
3. Open call: new research that has previously not been submitted elsewhere

Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this special issue. Authors can extend previously published conference or workshop papers; guidelines for this can be found in FAQ 9. Submissions shall be made through the Semantic Web journal website at http://www.semantic-web-journal.net. Prospective authors must take notice of the submission guidelines posted at http://www.semantic-web-journal.net/authors. We welcome any submission type as described http://www.semantic-web-journal.net/authors#types. While there is a soft limit of 25 pages, paper length must be justified by content.
Please indicate in the cover letter that it is for the Special Issue on “Large Language Models, Generative AI and Knowledge Graphs." All manuscripts will be reviewed based on the SWJ open and transparent review policy and will be made available online during the review process.
Also note that the Semantic Web journal is open access and all submissions rely on an open and transparent review process (see FAQ 1). Finally please note that submissions must comply with the journal’s Open Science Data requirements, which are detailed in the corresponding blog post.

Deadline

Submission deadline: 31st March 2025. Papers submitted before the deadline will be reviewed upon receipt.

Guest Editors

Oscar Corcho, Universidad Politécnica de Madrid, Spain
Daniel Garijo, Universidad Politécnica de Madrid, Spain
Paul Groth, University of Amsterdam, NL
Albert Meroño, King’s College London, UK
Elena Simperl, King’s College London, UK
Blerina Spahiu, Università degli Studi di Milano-Bicocca, IT
Valentina Tamma, University of Liverpool, UK
Raphaël Troncy, EURECOM, FR

Guest Editorial Board

TBC