Thank you very much, your answer clarified a lot.
So, the structure of the training dataset “defines” what the model learns. What I assume is, if the model is trained with a dataset which contains proper sentences, it is going to learn the structure and based on this identify entities. In the other case, where there is no structure, the model in order to identify the entity has to have already learned it by heart, because can only depend on the word it sees and not on the structure.
In my experiments I will try to give both kind of samples, with the majority consists of structured samples. I will inform you as soon as I have the error analysis.
Thank you once again.