I am reading some research paper on machine learning and come across below paragraph, can someone help me decode these two equations mentioned below. New to statistics and probability so apologies in advance if my question is very basic.

Here is an example showing the problem with unidentifiable models. The model p(x|y) is uniform for y ∈ {+1, −1}. Assuming with large amount of un- labeled data U we know p(x) is uniform in [0, 1]. We also have 2 labeled data points (0.1, +1), (0.9, −1). Can we determine the label for x = 0.5? No. With our assumptions we cannot distinguish the following two models:

p(y = 1) = 0.2, p(x|y = 1) = unif(0, 0.2), p(x|y = −1) = unif(0.2, 1)

p(y = 1) = 0.6, p(x|y = 1) = unif(0, 0.6), p(x|y = −1) = unif(0.6, 1)