Given the task definition, example input & output, solve the new input case.
In this task, you're given a review from Amazon and category of the product based on the review given by the user and your task is classify whether the given category match the review. Generate "True" if given review and its category match, otherwise generate "False".
Example: Review: Arrived broken. Manufacturer defect. Two of the legs of the base were not completely formed, so there was no way to insert the casters. I unpackaged the entire chair and hardware before noticing this. So, I'll spend twice the amount of time boxing up the whole useless thing and send it back with a 1-star review of part of a chair I never got to sit in. I will go so far as to include a picture of what their injection molding and quality assurance process missed though. I will be hesitant to buy again. It makes me wonder if there aren't missing structures and supports that don't impede the assembly process.
Category: furniture
Output: True
It's the correct category. Because the customer gives a review of the product which belongs to the furniture category, which we can see it from the way the customer describes his experience sharing how he unpackaged his chair.

New input case for you: Reviews: This camera is horrible compared to the original Q-See cameras I have. The light sensitivity is too sensitive. I used this camera inside the house (because image quality is so bad I moved the better cameras outside.) But even when lights are on, it just keeps flipping back and forth between night vision and regular color. I ended up just setting it to night only just to keep it from constantly switching back and forth. Inside I just need it to see if baby is asleep and ok. Quality is so bad you can't tell any kind of facial description of someone outside. These are far from any kind of HD quality
Category: pet_products
Output:
False