mlsanityData to 7 Oct 2026

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

arXiv 2302.00636 ↗First posted 1 Feb 2023cs.CLcited by 4

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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.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 9 of its 25 references that are in the map. First posted on arXiv 1 Feb 2023.

Builds on

9 of 25 references.

References · 9

  1. 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 719
  2. 2020Treebanking User-Generated Content: a UD Based Overview of Guidelines, Corpora and Unified Recommendationscited by 13
  3. 2022GCDT: A Chinese RST Treebank for Multigenre and Multilingual Discourse Parsingcited by 13
  4. 2022A Second Wave of UD Hebrew Treebanking and Cross-Domain Parsingcited by 10
  5. 2019All Roads Lead to UD: Converting Stanford and Penn Parses to English Universal Dependencies with Multilayer Annotationscited by 9
  6. 2020A Cross-Genre Ensemble Approach to Robust Reddit Part of Speech Taggingcited by 9
  7. 2021Genre as Weak Supervision for Cross-lingual Dependency Parsingcited by 8
  8. 2021Mischievous Nominal Constructions in Universal Dependenciescited by 7
  9. 2021Minor changes make a difference: a case study on the consistency of UD-based dependency parserscited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 1; 2026: 1.

4 papers.