DIAL-KG: Schema-Free Incremental Knowledge Graph Construction via Dynamic Schema Induction and Evolution-Intent Assessment
Weidong Bao, Yilin Wang, Ruyu Gao, Fangling Leng, Yubin Bao, and Ge Yu

TL;DR
DIAL-KG is a dynamic, schema-free framework for incremental knowledge graph construction that continuously updates and evolves schemas based on new data, improving quality and flexibility over static methods.
Contribution
It introduces a novel closed-loop framework with schema induction and evolution, enabling real-time, flexible knowledge graph updates without predefined schemas.
Findings
Achieves state-of-the-art quality in KG construction
Effectively induces and updates schemas dynamically
Maintains high fidelity and completeness of knowledge
Abstract
Knowledge Graphs (KGs) are foundational to applications such as search, question answering, and recommendation. Conventional knowledge graph construction methods are predominantly static, rely ing on a single-step construction from a fixed corpus with a prede f ined schema. However, such methods are suboptimal for real-world sce narios where data arrives dynamically, as incorporating new informa tion requires complete and computationally expensive graph reconstruc tions. Furthermore, predefined schemas hinder the flexibility of knowl edge graph construction. To address these limitations, we introduce DIAL KG, a closed-loop framework for incremental KG construction orches trated by a Meta-Knowledge Base (MKB). The framework oper ates in a three-stage cycle: (i) Dual-Track Extraction, which ensures knowledge completeness by defaulting to triple generation and switching to event extraction…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Graph Neural Networks · Topic Modeling · Graph Theory and Algorithms
