English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We present a system that automatically groups verb stems into inflection classes, performing a case study of Abui verbs. Starting from a relatively small number of fully glossed Abui sentences, we train a morphological precision grammar and use it to automatically analyze and gloss words from the unglossed portion of our corpus. Then we group stems into classes based on their cooccurrence patterns with several prefix series of interest. We compare our results to a curated collection of elicited examples and illustrate how our approach can be useful for field linguists as it can help them refine their analysis by accounting for more patterns in the data.

Computational Support for Finding Word Classes: A Case Study of Abui