mlsanityData to 7 Oct 2026

A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing

arXiv 2106.04222 ↗First posted 8 Jun 2021cs.CLcited by 5

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Abstract (arXiv)

We evaluate the efficacy of predicted UPOS tags as input features for dependency parsers in lower resource settings to evaluate how treebank size affects the impact tagging accuracy has on parsing performance. We do this for real low resource universal dependency treebanks, artificially low resource data with varying treebank sizes, and for very small treebanks with varying amounts of augmented data. We find that predicted UPOS tags are somewhat helpful for low resource treebanks, especially when fewer fully-annotated trees are available. We also find that this positive impact diminishes as the amount of data increases.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 6 of its 22 references that are in the map. First posted on arXiv 8 Jun 2021.

Builds on

6 of 22 references.

References · 6

  1. 2016Deep Biaffine Attention for Neural Dependency Parsingcited by 334
  2. 2015Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMscited by 10
  3. 2018An Investigation of the Interactions Between Pre-Trained Word Embeddings, Character Models and POS Tags in Dependency Parsingcited by 10
  4. 2020Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?cited by 9
  5. 2020Weakly Supervised POS Taggers Perform Poorly on Truly Low-Resource Languagescited by 7
  6. 2020On the Frailty of Universal POS Tags for Neural UD Parserscited by 4

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Citing papers per year: 2022: 2; 2023: 2; 2024: 0; 2025: 1.

5 papers.