  Creating a descriptive grammar of a language is an indispensable step for
language documentation and preservation. However, at the same time it is a
tedious, time-consuming task. In this paper, we take steps towards automating
this process by devising an automated framework for extracting a first-pass
grammatical specification from raw text in a concise, human- and
machine-readable format. We focus on extracting rules describing agreement, a
morphosyntactic phenomenon at the core of the grammars of many of the world's
languages. We apply our framework to all languages included in the Universal
Dependencies project, with promising results. Using cross-lingual transfer,
even with no expert annotations in the language of interest, our framework
extracts a grammatical specification which is nearly equivalent to those
created with large amounts of gold-standard annotated data. We confirm this
finding with human expert evaluations of the rules that our framework produces,
which have an average accuracy of 78%. We release an interface demonstrating
the extracted rules at https://neulab.github.io/lase/.
