  In recent years, a flurry of morphological datasets had emerged, most notably
UniMorph, a multi-lingual repository of inflection tables. However, the flat
structure of the current morphological annotation schema makes the treatment of
some languages quirky, if not impossible, specifically in cases of polypersonal
agreement, where verbs agree with multiple arguments using true affixes. In
this paper, we propose to address this phenomenon by expanding the UniMorph
annotation schema to a hierarchical feature structure that naturally
accommodates complex argument marking. We apply this extended schema to one
such language, Georgian, and provide a human-verified, accurate and balanced
morphological dataset for Georgian verbs. The dataset has 4 times more tables
and 6 times more verb forms compared to the existing UniMorph dataset, covering
all possible variants of argument marking, demonstrating the adequacy of our
proposed scheme. Experiments with a standard reinflection model show that
generalization is easy when the data is split at the form level, but extremely
hard when splitting along lemma lines. Expanding the other languages in
UniMorph to this schema is expected to improve both the coverage, consistency
and interpretability of this benchmark.
