Do gensim Doc2Vec distinguish between same Sentence with positive and negative context.?
use textblob and set the sentiment and polarity for each sentence. tokenize the sentences using nlp
While learning Doc2Vec library, I got stuck on the following question.
Do gensim Doc2Vec distinguish between the same Sentence with positive and negative context?
For Example:
Sentence A: "I love Machine Learning"
Sentence B: "I do not love Machine Learning"
If I train sentence A and B with doc2vec and find cosine similarity between their vectors:

Will the model be able to distinguish the sentence and give a cosine similarity very less than 1 or negative?
Or Will the model represent both the sentences very close in vector space and give cosine similarity close to 1, as mostly all the words are same except the negative word (do not).

Also, If I train only on sentence A and try to infer Sentence B, will both vectors be close to each other in vector space.?
I would request the NLP community and Doc2Vec experts for helping me out in understanding this.
Thanks in Advance !!