  The CoNLL--SIGMORPHON 2018 shared task on supervised learning of
morphological generation featured data sets from 103 typologically diverse
languages. Apart from extending the number of languages involved in earlier
supervised tasks of generating inflected forms, this year the shared task also
featured a new second task which asked participants to inflect words in
sentential context, similar to a cloze task. This second task featured seven
languages. Task 1 received 27 submissions and task 2 received 6 submissions.
Both tasks featured a low, medium, and high data condition. Nearly all
submissions featured a neural component and built on highly-ranked systems from
the earlier 2017 shared task. In the inflection task (task 1), 41 of the 52
languages present in last year's inflection task showed improvement by the best
systems in the low-resource setting. The cloze task (task 2) proved to be
difficult, and few submissions managed to consistently improve upon both a
simple neural baseline system and a lemma-repeating baseline.
