  Recent approaches have attempted to personalize dialogue systems by
leveraging profile information into models. However, this knowledge is scarce
and difficult to obtain, which makes the extraction/generation of profile
information from dialogues a fundamental asset. To surpass this limitation, we
introduce the Profile Generation Task (PGTask). We contribute with a new
dataset for this problem, comprising profile sentences aligned with related
utterances, extracted from a corpus of dialogues. Furthermore, using
state-of-the-art methods, we provide a benchmark for profile generation on this
novel dataset. Our experiments disclose the challenges of profile generation,
and we hope that this introduces a new research direction.
