Hi everyone,
I’m trying to realize a Resume Parser through a NER task using BERT, so it would be a token level classification task.
Now, I have a problem with the Work Experience section of the resume.
I would like to extract (date, job title, company name, job description).
The problem is that while the first three are entities with few words, the last one is made up of many words, so I don’t think a token level classification is ok, because I should associate a description entity for each word of the description (I think it would be not efficient).
The ideal solution should be a sentence classification for the description, so for the entire description I would associate only a label.
But in this way, BERT should perform a token & sentence classification at the same time, and I don’t know if this feasible.
I don’t want use two BERT, one for token and the other one for sentence.
Is it possible to perform the two tasks at the same time with just one network?
Many thanks in advance