Third-party cyber evaluations involving OpenAI models
openai.com·14h ago
AI Research
arXiv CS.AI·Jun 29·5 min read
KG2Cypher: Data-Centric Pipeline for Building Enterprise Text-to-Cypher Systems
TL;DR
Many enterprises struggle to convert unstructured text data into structured formats for analysis. KG2Cypher is a data-centric pipeline designed to automate the transformation of text into Cypher queries, which are used in graph databases.
✦ Why It Matters
Engineers can leverage KG2Cypher to automate text data integration, enhancing efficiency in data analysis workflows.
Key Takeaways
- Explore KG2Cypher for building text-to-Cypher systems.
- Utilize LLMs for generating natural-language questions from graph data.
- Validate Text-Cypher pairs with both LLM and human assessments.
- Leverage improvements in execution accuracy for enterprise queries.
How It Works
KG2Cypher constructs Cypher queries from observed graph facts and uses LLMs to generate natural-language questions. It validates these pairs through LLM and human judges, ensuring high-quality data for training.
The system employs class-conditioned schema prompting and entity retrieval to enhance query generation, while LoRA-based inference optimizes performance.