Ambiguity: Many words and phrases can have multiple interpretations and could be considered as different entity types in different contexts.
Variability: Entities can appear in different forms (e.g., singular vs. plural, different spellings, abbreviations), and some entities may have multiple names or aliases.
Rare entities: Some entities may be rare or unseen in the training data, which makes it difficult for the model to learn to recognize them accurately.
Entity boundaries: Determining the exact boundaries of an entity within a text can be challenging, especially when entities are mentioned in complex or ambiguous ways.