CHisAgent: A Multi-Agent Framework for Event Taxonomy Construction in Ancient Chinese Cultural Systems

arXiv:2601.05520 · cs.CL · Submitted 2026-01-09 · Read on arXiv

cs.CL

Submitted: 2026-01-09

Updated: 2026-10-07

Code: https://github.com/tangxuemei1995/Ancient-chinese-segmenter

Terminology

• Ontology — 18× in this paper · explained in 2 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Semantic Similarity — 7× in this paper · explained in 2 episodes
• Clustering — 5× in this paper · explained in 2 episodes
• Core — 5× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Abstraction — 3× in this paper · explained in 1 episode
• Actor — 3× in this paper · explained in 3 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Multi-Agent Framework — 3× in this paper · explained in 3 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Evaluation Dimensions — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Knowledge Graph — 1× in this paper · explained in 7 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Multi-agent Collaboration — 1× in this paper · explained in 2 episodes

Sources

• An Investigation into Value Misalignment in LLM-Generated Texts for Cultural Heritage
• BERTopic: Neural topic modeling with a class-based TF-IDF procedure
• TaxoAdapt: Aligning LLM-Based Multidimensional Taxonomy Construction to Evolving Research Corpora
• Building Data-Driven Occupation Taxonomies: A Bottom-Up Multi-Stage Approach via Semantic Clustering and Multi-Agent Collaboration
• Reference-Free Evaluation of Taxonomies
• Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples

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