# CommonMorph: Participatory Morphological Documentation Platform

arXiv: https://arxiv.org/abs/2604.04515 · HTML: https://mlsanity.com/paper/2604.04515/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 27 references that are in the map.
- First posted on arXiv 6 Apr 2026.

## Builds on (most cited first, 6 of 6)

- [Large Language Models for Data Annotation and Synthesis: A Survey](https://mlsanity.com/paper/2402.13446/) (2024)
- [The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection](https://mlsanity.com/paper/1910.11493/) (2019)
- [UniMorph 2.0: Universal Morphology](https://mlsanity.com/paper/1810.11101/) (2018)
- [Neural Transductive Learning and Beyond: Morphological Generation in the Minimal-Resource Setting](https://mlsanity.com/paper/1809.08733/) (2018)
- [Dia-Lingle: A Gamified Interface for Dialectal Data Collection](https://mlsanity.com/paper/2509.26210/) (2025)
- [Can a Neural Model Guide Fieldwork? A Case Study on Morphological Data Collection](https://mlsanity.com/paper/2409.14628/) (2024)

## Abstract (arXiv)

Collecting and annotating morphological data present significant challenges, requiring linguistic expertise, methodological rigour, and substantial resources. These barriers are particularly acute for low-resource languages and varieties. To accelerate this process, we introduce textttCommonMorph, a comprehensive platform that streamlines morphological data collection development through a three-tiered approach: expert linguistic definition, contributor elicitation, and community validation. The platform minimises manual work by incorporating active learning, annotation suggestions, and tools to import and adapt materials from related languages. It accommodates diverse morphological systems, including fusional, agglutinative, and root-and-pattern morphologies. Its open-source design and UniMorph-compatible outputs ensure accessibility and interoperability with NLP tools. Our platform is accessible at https://common-morph.com, offering a replicable model for preserving linguistic diversity through collaborative technology.