Given the task definition, example input & output, solve the new input case.
In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no".
Example: Review: For a movie that gets no respect there sure are a lot of memorable quotes listed for this gem. Imagine a movie where Joe Piscopo is actually funny! Maureen Stapleton is a scene stealer. The Moroni character is an absolute scream. Watch for Alan The Skipper Hale jr. as a police Sgt. Question: is it a positive review?
Output: yes
There is an expression of appreciation in this movie review, hence we can say it's positive. So generated label is 'yes'.

New input case for you: Review: I have never commented on a film before. I watched this movie with my girlfriend last night. I've read comments saying this movie stays with you. It does. It's been almost 24 hours and I am still completely affected. This movie left me questioning my own self. How can I possibly compare myself to a character such as Ben who is totally selfless. I loved this movie. I love movies that keep me guessing and wondering until the end. I feel two emotions predominantly, happiness and sadness. An amazing feel good movie and a very sad one too. I so wanted Ben and Emily to be together, but in the end, they were, forever. If you haven't seen this movie, get it and watch it. Just make sure you have no distractions. You'll want to see every nuance in this picture. One for my library. Question: is it a negative review?
Output:
no