  This paper deals with the problem of soft guessing under log-loss distortion
(logarithmic loss) that was recently investigated by [Wu and Joudeh, IEEE ISIT,
pp. 466--471, 2023]. We extend this problem to soft guessing allowing errors,
i.e., at each step, a guesser decides whether to stop the guess or not with
some probability and if the guesser stops guessing, then the guesser declares
an error. We show that the minimal expected value of the cost of guessing under
the constraint of the error probability is characterized by the smooth R\'enyi
entropy. Furthermore, we carry out an asymptotic analysis for a stationary and
memoryless source.
