ProgGen: Generating Named Entity Recognition Datasets Step-by-step with Self-Reflexive Large Language Models
Open Access
- 1 January 2024
- conference paper
- Published by Association for Computational Linguistics (ACL)
- p. 15992-16030
Abstract
Yuzhao Heng, Chunyuan Deng, Yitong Li, Yue Yu, Yinghao Li, Rongzhi Zhang, Chao Zhang. Findings of the Association for Computational Linguistics ACL 2024. 2024.Keywords
All Related Versions
This publication has 7 references indexed in Scilit:
- Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction2023
- Can Synthetic Text Help Clinical Named Entity Recognition? A Study of Electronic Health Records in French2023
- Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions2023
- RelationPrompt: Leveraging Prompts to Generate Synthetic Data for Zero-Shot Relation Triplet Extraction2022
- Few-Shot Named Entity Recognition: An Empirical Baseline Study2021
- Constrained Labeled Data Generation for Low-Resource Named Entity Recognition2021
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding2019