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 tried restarting the movie twice. I put it in three machines to see what was wrong. Did Steven Seagal's voice change? Did he die during filming and the studio have to dub the sound with someone who doesn't even resemble him? Or was the sound on the DVD destroyed? After about 10 minutes, you finally hear the actor's real voice. Though throughout most of the film, it sounds like the audio was recorded in a bathroom.I would be ashamed to donate a copy of this movie to Goodwill, if I owned a copy. I rented it, but I will never do that again. I will check this database before renting any more of his movies, all of which were (more or less) good movies. You usually knew what you were getting when you watched a Steven Seagal movie. I guess that is no more. Question: is it a negative review?
Output:
yes