Update README.md

README.md

@@ -24,6 +24,7 @@ The GENRE (Generative ENtity REtrieval) system as presented in [Autoregressive E
 
 In a nutshell, GENRE uses a sequence-to-sequence approach to entity retrieval (e.g., linking), based on fine-tuned [BART](https://arxiv.org/abs/1910.13461) architecture. GENRE performs retrieval generating the unique entity name conditioned on the input text using constrained beam search to only generate valid identifiers. The model was first released in the [facebookresearch/GENRE](https://github.com/facebookresearch/GENRE) repository using `fairseq` (the `transformers` models are obtained with a conversion script similar to [this](https://github.com/huggingface/transformers/blob/master/src/transformers/models/bart/convert_bart_original_pytorch_checkpoint_to_pytorch.py).
 
+This model was trained on the full training set of [KILT](https://arxiv.org/abs/2009.02252) (i.e., 11 datasets for fact-checking, entity-linking, slot filling, dialogue, open-domain extractive and abstractive QA).
 
 ## BibTeX entry and citation info