# Are UD Treebanks Getting More Consistent? A Report Card for English UD

arXiv: https://arxiv.org/abs/2302.00636 · HTML: https://mlsanity.com/paper/2302.00636/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 25 references that are in the map.
- First posted on arXiv 1 Feb 2023.

## Builds on (most cited first, 9 of 9)

- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [GCDT: A Chinese RST Treebank for Multigenre and Multilingual Discourse Parsing](https://mlsanity.com/paper/2210.10449/) (2022)
- [Treebanking User-Generated Content: a UD Based Overview of Guidelines, Corpora and Unified Recommendations](https://mlsanity.com/paper/2011.02063/) (2020)
- [A Second Wave of UD Hebrew Treebanking and Cross-Domain Parsing](https://mlsanity.com/paper/2210.07873/) (2022)
- [All Roads Lead to UD: Converting Stanford and Penn Parses to English Universal Dependencies with Multilayer Annotations](https://mlsanity.com/paper/1909.00522/) (2019)
- [A Cross-Genre Ensemble Approach to Robust Reddit Part of Speech Tagging](https://mlsanity.com/paper/2004.14312/) (2020)
- [Genre as Weak Supervision for Cross-lingual Dependency Parsing](https://mlsanity.com/paper/2109.04733/) (2021)
- [Mischievous Nominal Constructions in Universal Dependencies](https://mlsanity.com/paper/2108.12928/) (2021)
- [Minor changes make a difference: a case study on the consistency of UD-based dependency parsers](https://mlsanity.com/paper/2111.15413/) (2021)

## Built on by (most cited first, 4 of 4)

- [Why Can't Discourse Parsing Generalize? A Thorough Investigation of the Impact of Data Diversity](https://mlsanity.com/paper/2302.06488/) (2023)
- [MaiBaam: A Multi-Dialectal Bavarian Universal Dependency Treebank](https://mlsanity.com/paper/2403.10293/) (2024)
- [Building UD Cairo for Old English in the Classroom](https://mlsanity.com/paper/2504.18718/) (2025)
- [Syntactic Belief Update as the Driver of Garden Path Processing Difficulty](https://mlsanity.com/paper/2606.27206/) (2026)

## Abstract (arXiv)

Recent efforts to consolidate guidelines and treebanks in the Universal Dependencies project raise the expectation that joint training and dataset comparison is increasingly possible for high-resource languages such as English, which have multiple corpora. Focusing on the two largest UD English treebanks, we examine progress in data consolidation and answer several questions: Are UD English treebanks becoming more internally consistent? Are they becoming more like each other and to what extent? Is joint training a good idea, and if so, since which UD version? Our results indicate that while consolidation has made progress, joint models may still suffer from inconsistencies, which hamper their ability to leverage a larger pool of training data.