# Marrying Universal Dependencies and Universal Morphology

arXiv: https://arxiv.org/abs/1810.06743 · HTML: https://mlsanity.com/paper/1810.06743/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Oct 2018.

## Built on by (most cited first, 11 of 11)

- [On the Pitfalls of Analyzing Individual Neurons in Language Models](https://mlsanity.com/paper/2110.07483/) (2021)
- [Probing the Emergence of Cross-lingual Alignment during LLM Training](https://mlsanity.com/paper/2406.13229/) (2024)
- [Same Neurons, Different Languages: Probing Morphosyntax in Multilingual Pre-trained Models](https://mlsanity.com/paper/2205.02023/) (2022)
- [Probing as Quantifying Inductive Bias](https://mlsanity.com/paper/2110.08388/) (2021)
- [UniMorph 4.0: Universal Morphology](https://mlsanity.com/paper/2205.03608/) (2022)
- [Evaluating the Morphosyntactic Well-formedness of Generated Texts](https://mlsanity.com/paper/2103.16590/) (2021)
- [A Latent-Variable Model for Intrinsic Probing](https://mlsanity.com/paper/2201.08214/) (2022)
- [A Joint Matrix Factorization Analysis of Multilingual Representations](https://mlsanity.com/paper/2310.15513/) (2023)
- [Morphological Processing of Low-Resource Languages: Where We Are and What's Next](https://mlsanity.com/paper/2203.08909/) (2022)
- [Cross-lingual Inflection as a Data Augmentation Method for Parsing](https://mlsanity.com/paper/2205.09350/) (2022)
- [Zero-Shot Morphological Discovery in Low-Resource Bantu Languages via Cross-Lingual Transfer and Unsupervised Clustering](https://mlsanity.com/paper/2604.22723/) (2026)

## Abstract (arXiv)

The Universal Dependencies (UD) and Universal Morphology (UniMorph) projects each present schemata for annotating the morphosyntactic details of language. Each project also provides corpora of annotated text in many languages - UD at the token level and UniMorph at the type level. As each corpus is built by different annotators, language-specific decisions hinder the goal of universal schemata. With compatibility of tags, each project's annotations could be used to validate the other's. Additionally, the availability of both type- and token-level resources would be a boon to tasks such as parsing and homograph disambiguation. To ease this interoperability, we present a deterministic mapping from Universal Dependencies v2 features into the UniMorph schema. We validate our approach by lookup in the UniMorph corpora and find a macro-average of 64.13% recall. We also note incompatibilities due to paucity of data on either side. Finally, we present a critical evaluation of the foundations, strengths, and weaknesses of the two annotation projects.