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