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 was really stunned how much a film, that's over 60 years old could impress me. It is nearly two hours long, there are absolutely no stars in it, there are subtitles but nevertheless it is interesting and exciting to watch. What impressed me mostly was the realism of the film. You could nearly feel the coldness of the ice, because you could see that the storms are real. This is a relief in a CGI-world like ourdays. I wondered how much work this must have been for van Dyke. I read somewhere that it took 17 months to film it. Now who wants to talk about 'Titanic' anymore? It's a great film with a great message and I would recommend it to future directors to see how great and realistic movies can be if they are only directed with realism instead of visual effects. Question: is it a negative review?
Output:
no