Chatty-KG: A Multi-Agent AI System for On-Demand Conversational Question Answering over Knowledge Graphs
Summary: Chatty-KG: modular multi-agent conversational KGQA; task-specialized LLM agents do context tracking, entity/relation linking, and query planning to synthesize SPARQL, preserving KG structure vs serialized-RAG. Supports on-demand, low-latency multi-turn QA over evolving/private KGs, with strong F1/P@1 gains. (summarized by gpt-5.4-mini on Apr 11 2026)
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Authors
- 1. Reham Omar
- 2. Abdelghny Orogat
- 3. Ibrahim Abdelaziz
- 4. Omij Mangukiya
- 5. Panos Kalnis
- 6. Essam Mansour
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,211 | Natural Language Question Answering over RDF — A Graph Data Driven Approach | 2014 | SIGMOD | 7.3743561e-05 |
| 9,875 | A Universal Question-Answering Platform for Knowledge Graphs | 2023 | SIGMOD | 4.2667743e-05 |
| 10,374 | Dialogue Benchmark Generation from Knowledge Graphs with Cost-Effective Retrieval-Augmented LLMs | 2025 | SIGMOD | 4.1945683e-05 |
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