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Poster: ChatIYP: Enabling Natural Language Access to the Internet Yellow Pages Database

arXiv 2509.19411 ↗First posted 23 Sep 2025cs.NI cs.HC cs.LGcited by 0

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Abstract (arXiv)

The Internet Yellow Pages (IYP) aggregates information from multiple sources about Internet routing into a unified, graph-based knowledge base. However, querying it requires knowledge of the Cypher language and the exact IYP schema, thus limiting usability for non-experts. In this paper, we propose ChatIYP, a domain-specific Retrieval-Augmented Generation (RAG) system that enables users to query IYP through natural language questions. Our evaluation demonstrates solid performance on simple queries, as well as directions for improvement, and provides insights for selecting evaluation metrics that are better fit for IYP querying AI agents.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 10 references that are in the map. First posted on arXiv 23 Sep 2025.

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References · 3

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  3. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276

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  1. 2025Learning to Route: A Rule-Driven Agent Framework for Hybrid-Source Retrieval-Augmented Generation
  2. 2025A Knowledge Graph and a Tripartite Evaluation Framework Make Retrieval-Augmented Generation Scalable and Transparent
  3. 2024Retrieval-Augmented Generation for Natural Language Processing: A Survey
  4. 2024WeKnow-RAG: An Adaptive Approach for Retrieval-Augmented Generation Integrating Web Search and Knowledge Graphs
  5. 2025Comparative Analysis of Neural Retriever-Reranker Pipelines for Retrieval-Augmented Generation over Knowledge Graphs in E-commerce Applications
  6. 2024Text2SQL is Not Enough: Unifying AI and Databases with TAG
  7. 2026Reducing Hallucinations in Complex Question Answering using Simple Graph-based Retrieval-Augmented Generation (long version)
  8. 2025Graph-Enhanced Retrieval-Augmented Question Answering for E-Commerce Customer Support