I am trying to write a model that will extract certain details from financial documents.It must be able to extract the; contract start date, contract duration, contract value and all named entities. Preferably it would also be able to categorise the named entities.I have roughly 600 tagged documents that I can use for training and testing purposes.What model should I use?I have had a look at different named entity recognition models, such as the Skip-Gram model. However these models do not utilise the fact that each one of these documents will contain all of this information. To illustrate this, the Skip-Gram model is often implemented in such a way that only the words in the same sentence contribute to its semantic vector.
What algorithm to use for a specific 'Named Entity Recognition'/'Information extraction' problem
information retrieval;named entity recognition