How do I calculate the semantic similarity between two n-grams?
Cosine similarity might be useful if you average both word vectors in a bi-gram first. So you want to take the vector for 'his' and 'name', average them into one vector. Then take the vector for 'I' and 'am' and average them into one vector. Finally, calculate cosine similarity for both resulting vectors and it should give you a rough semantic similarity.
I'm trying to calculate the semantic similarity between two bi-grams and I need to use fasttext's pre-trained word vectors to accomplish this task. 
For ex :
The b-grams are python lists of two elements:
[his, name] and [I, am] 
They are two tuples and I need to calculate the similarity between these two tuples by any means necessary.
I'm hoping there's a score which can give me a good approximation of similarity.
For ex - If there are methods which can tell me that [His, name] is more similar to [I, am] than [An, apple].
Right now I only made use of cosine similarity which does include any semantic similarity.