Update README.md

README.md

@@ -18,7 +18,7 @@ NuNER Zero is a zero-shot Named Entity Recognition (NER) Model. For few-shot lea
 
 NuNER Zero uses a variation of the [GLiNER](https://huggingface.co/papers/2311.08526) architecture, and takes the same input (concatenation entity types and text).
 
-Unlike GliNER, NuNER Zero is a token classifier: it returns the infered probabilities for each token to belong to each entity type. You need to merge consecutive tokens that have a probability >50% to obtain the entities.
+Unlike GliNER, NuNER Zero is a token classifier: it returns the infered probabilities for each token to belong to each entity type. This allow to remove the limit size of detected entities.
 
 NuNER Zero was trained on NuNER v2.0 dataset, which combines subsets of Pile and C4 annotated via LLMs using [NuNER's procedure](https://huggingface.co/papers/2402.15343).