A5089571454- Natural Language Processing
- Semantic Web and Ontology Development
- Management and Reproducibility of Scientific Workflows
- Statistical Machine Translation and Natural Language Processing
- Data Quality Assessment and Improvement
- Data Sharing and Stewardship in Science
- Graph Neural Network Models and Applications
Universität Hamburg
2023
This paper presents a scholarly Knowledge Graph Question Answering (KGQA) that answers bibliographic natural language questions by leveraging large model (LLM) in few-shot manner. The initially identifies the top-n similar training related to given test question via BERT-based sentence encoder and retrieves their corresponding SPARQL. Using question-SPARQL pairs as an example creates prompt. Then pass prompt LLM generate Finally, runs SPARQL against underlying KG - ORKG (Open Research KG)...
This paper introduces a scholarly Question Answering (QA) system on top of the NFDI4DataScience Gateway, employing Retrieval Augmented Generation-based (RAG) approach. The NFDI4DS as foundational framework, offers unified and intuitive interface for querying various scientific databases using federated search. RAG-based QA, powered by Large Language Model (LLM), facilitates dynamic interaction with search results, enhancing filtering capabilities fostering conversational engagement Gateway...
©NFDI4DataScience (NFDI4DS) is a consortium to support researchers in all stages of the research data lifecycle conduct their line with FAIR principles. The developed infrastructure targets from wide range disciplines science and AI. We present ideas NFDI4DS gateway portal. Two approaches navigate digital objects (articles, data, machine learning models, workflows, scripts/code, etc.) various resources such as ORKG, DBLP database, other knowledge graphs (KGs). Transparency, reproducibility,...