A Unified Taxonomy-Guided Instruction Tuning Framework for Entity Set Expansion and Taxonomy Expansion

Entity set expansion, taxonomy expansion, and seed-guided taxonomy construction are three representative tasks for automatically enriching an existing taxonomy with emerging concepts. Previous studies have treated them as separate tasks, leading to techniques that are specialized for one task but lack generalizability and a holistic perspective. In this paper, we propose a unified solution to address all three tasks. Specifically, we identify two fundamental skills facilitating the three tasks: finding "siblings" and finding "parents". To this end, we introduce a taxonomy-guided instruction tuning framework that trains a large language model to generate siblings and parents for query entities, where the joint pretraining process enables mutual reinforcement of these two skills. Extensive experiments on multiple benchmark datasets validate the effectiveness of our proposed TAXOINSTRUCT framework, demonstrating its superiority over task-specific baselines across all three tasks. Our codes and data are available at https: //github.com/yanzhen4/TaxoInstruct .