Model Card for LLMAEL-ReFinED-FT

We introduce LLMAEL (LLM-Augmented Entity Linking), a pipeline method to enhance entity linking through LLM data augmentation. We release our customly fine-tuned LLMAEL-ReFinED-FT model, which is fine-tuned from the ReFinED EL model using an Llama-3-70b augmented version of the AIDA_train dataset. LLMAEL-ReFinED-FT yields new SOTA results across six standard EL benchmarks: AIDA_test, MSNBC, AQUAINT, ACE2004, WNED-CLUEWEB, and WNED-WIKIPEDIA, achieving an average 1.21% accuracy gain.

For more details, refer to our paper 📖 LLMAEL: Large Language Models are Good Context Augmenters for Entity Linking

Model Description

  • Developed by: Amy Xin, Yunjia Qi, Zijun Yao, Fangwei Zhu, Kaisheng Zeng, Bin Xu, Lei Hou, Juanzi Li
  • Model type: Entity Linking Model
  • Language(s): English
  • Finetuned from model [optional]: ReFinED
Downloads last month
12
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API: The model has no pipeline_tag.

Dataset used to train THU-KEG/LLMAEL-ReFinED-FT