UniMorph 4.0: Universal Morphology
Abstract
The Universal Morphology (UniMorph) project is a collaborative effort providing broad-coverage instantiated normalized morphological inflection tables for hundreds of diverse world languages. The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema. This paper presents the expansions and improvements made on several fronts over the last couple of years (since McCarthy et al. (2020)). Collaborative efforts by numerous linguists have added 67 new languages, including 30 endangered languages. We have implemented several improvements to the extraction pipeline to tackle some issues, e.g. missing gender and macron information. We have also amended the schema to use a hierarchical structure that is needed for morphological phenomena like multiple-argument agreement and case stacking, while adding some missing morphological features to make the schema more inclusive. In light of the last UniMorph release, we also augmented the database with morpheme segmentation for 16 languages. Lastly, this new release makes a push towards inclusion of derivational morphology in UniMorph by enriching the data and annotation schema with instances representing derivational processes from MorphyNet.
Cite
@article{arxiv.2205.03608,
title = {UniMorph 4.0: Universal Morphology},
author = {Khuyagbaatar Batsuren and Omer Goldman and Salam Khalifa and Nizar Habash and Witold Kieraś and Gábor Bella and Brian Leonard and Garrett Nicolai and Kyle Gorman and Yustinus Ghanggo Ate and Maria Ryskina and Sabrina J. Mielke and Elena Budianskaya and Charbel El-Khaissi and Tiago Pimentel and Michael Gasser and William Lane and Mohit Raj and Matt Coler and Jaime Rafael Montoya Samame and Delio Siticonatzi Camaiteri and Benoît Sagot and Esaú Zumaeta Rojas and Didier López Francis and Arturo Oncevay and Juan López Bautista and Gema Celeste Silva Villegas and Lucas Torroba Hennigen and Adam Ek and David Guriel and Peter Dirix and Jean-Philippe Bernardy and Andrey Scherbakov and Aziyana Bayyr-ool and Antonios Anastasopoulos and Roberto Zariquiey and Karina Sheifer and Sofya Ganieva and Hilaria Cruz and Ritván Karahóǧa and Stella Markantonatou and George Pavlidis and Matvey Plugaryov and Elena Klyachko and Ali Salehi and Candy Angulo and Jatayu Baxi and Andrew Krizhanovsky and Natalia Krizhanovskaya and Elizabeth Salesky and Clara Vania and Sardana Ivanova and Jennifer White and Rowan Hall Maudslay and Josef Valvoda and Ran Zmigrod and Paula Czarnowska and Irene Nikkarinen and Aelita Salchak and Brijesh Bhatt and Christopher Straughn and Zoey Liu and Jonathan North Washington and Yuval Pinter and Duygu Ataman and Marcin Wolinski and Totok Suhardijanto and Anna Yablonskaya and Niklas Stoehr and Hossep Dolatian and Zahroh Nuriah and Shyam Ratan and Francis M. Tyers and Edoardo M. Ponti and Grant Aiton and Aryaman Arora and Richard J. Hatcher and Ritesh Kumar and Jeremiah Young and Daria Rodionova and Anastasia Yemelina and Taras Andrushko and Igor Marchenko and Polina Mashkovtseva and Alexandra Serova and Emily Prud'hommeaux and Maria Nepomniashchaya and Fausto Giunchiglia and Eleanor Chodroff and Mans Hulden and Miikka Silfverberg and Arya D. McCarthy and David Yarowsky and Ryan Cotterell and Reut Tsarfaty and Ekaterina Vylomova},
journal= {arXiv preprint arXiv:2205.03608},
year = {2022}
}
Comments
LREC 2022; The first two authors made equal contributions