2021/06/08 by Mark Anderson, Anderson, Mark, Mathieu Dehouck +3 · 1 citation
Computer Science · #Computation and Language (cs.CL) #Data Mining Algorithms and Applications #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2106.04222
openalex publication_date 2021/06/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We evaluate the efficacy of predicted UPOS tags as input features for\ndependency parsers in lower resource settings to evaluate how treebank size\naffects the impact tagging accuracy has on parsing performance. We do this for\nreal low resource universal dependency treebanks, artificially low resource\ndata with varying treebank sizes, and for very small treebanks with varying\namounts of augmented data. We find that predicted UPOS tags are somewhat\nhelpful for low resource treebanks, especially when fewer fully-annotated trees\nare available. We also find that this positive impact diminishes as the amount\nof data increases.\n