Hi everyone, I’m using pretrain word embedding for nmt task. I have idea about using word features such as named entity to improve nmt quality. Is it possible to concate one hot vector (named entity) to my pretrain word embedding and use it for my nmt model ?
For example:
Given sentence: My name is James .
NE annotated sentence: My|O name|O is|O James|PERSON
With James|PERSON, i will concate one-hot vector of PERSON tag (e.g [1,0,0,0]) to word embedding vector of “James” (e.g [4,5,6]). So result is [4,5,6,1,0,0,0]