The stick is first broken into two pieces. The longest (or rather, not the shortest) is then broken into two.
Assume that the shorter piece is represented by the vertical perpendicular to PPc. Then, as above, P must lie below the vertical edge of the medial triangle. Which means that in this case, in order that the three pieces could form a triangle, P should lie inside of one (still the medial) of the three triangles. This has 1 chance in three with the probability of 1/3.
Easy, is not it? However, there is a pitfall which is often missed. I have missed it first as did M. Gardner's in a Scientific American article. The article was later included in his collection The Colossal Book of Mathematics (Chapter 21), wherein an Addendum he has corrected the mishap. (M. Gardner also cites a respectable textbook that was also guilty of the same error.)
The situation now is a little more complicated than in the first problem. Even though the three triangles at hand have equal areas as before, the probability, in this case, is not distributed uniformly over the triangle. This is because the second point is being chosen randomly over a piece shorter than the whole stick, so it can't be thought of as being uniformly distributed over the original length. An observation to this effect has been made by Joe Whittaker in 1990. His reasoning was based on diagrams drawn in Cartesian coordinates and probabilities distributed in a square. (The problem has been also treated in Challenging Mathematical Problems With Elementary Solutions by the Yaglom brothers and in an online discussion.)
Below, I offer a treatment of the problem based on a triangular diagram.

Assume that after the first break the pieces have lengths h and (1-h), with h < (1-h), i.e. h < 1/2, as expected. With h fixed, we randomlly (and uniformly) break the piece of length (1-h). The probability that the three pieces thus obtained will form a triangle clearly depends on h. It is small if h is small, and it is nearing 1 for h close to 1/2. More accurately, this probability is equal to the ratio VW/UZ, but:
The total probability is given as the integral of the expression in (*) from 0 to 1/2, i.e., over the range of eligible h:
The probability we are looking for is the conditional probability obtained under the assumption that h < 1/2. Thus the integral must be divided by 1/2. The result, 2·ln(2) - 1, is approximately equal to 0.386, is slightly more than 1/3, and has been verified experimentally.
I am indebted to Orion Elenzil for questioning the original line of reasoning and for drawing my attention to the discrepancy between the original derivation and experimental data.