To elaborate on @Media's answer, what is meant by "I think that the numbers make sense only if they're actually 227 by 227" is the following:
In the attached snapshot, the size of the 1st convolution layer is $55x55$. Now suppose the dimensions of the input images are $224x224$, then by applying the $11x11$ kernels with $stride=4$ as described in the paper, would result in:
$outsize=\frac{(insize+2*padding-kernel)}{stride}+1$
$outsize=\frac{(224+2*0-11)}{4}+1=54.25$
Whereas if the dimensions were $227x227$, then that would result in:
$outsize=\frac{(227+2*0-11)}{4}+1=55$
which conforms with the size of the 1st convolution layer described in the paper.
* I got the formula for calculating the output size from this YouTube tutorial.