3 citations · 3 across the 7 of their papers we have counts for
13 papers
Parsing linearizations appreciate PoS tags - but some are fussy about errors
Alberto Muñoz-Ortiz, Mark Anderson, David Vilares +1
PoS tags, once taken for granted as a useful resource for syntactic parsing, have become more situational with the popularization of deep learning. Recent work on the impact of PoS…
The Impact of Edge Displacement Vaserstein Distance on UD Parsing Performance
Mark Anderson, Carlos Gómez-Rodríguez
We contribute to the discussion on parsing performance in NLP by introducing a measurement that evaluates the differences between the distributions of edge displacement (the direct…
Assessing the Limits of the Distributional Hypothesis in Semantic Spaces: Trait-based Relational Knowledge and the Impact of Co-occurrences
Mark Anderson, Jose Camacho-Collados
The increase in performance in NLP due to the prevalence of distributional models and deep learning has brought with it a reciprocal decrease in interpretability. This has spurred…
Splitting EUD graphs into trees: A quick and clatty approach
Mark Anderson, Carlos Gómez-Rodríguez
We present the system submission from the FASTPARSE team for the EUD Shared Task at IWPT 2021. We engaged in the task last year by focusing on efficiency. This year we have focused…
A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021
Mark Anderson, Carlos Gómez Rodríguez
We evaluate three leading dependency parser systems from different paradigms on a small yet diverse subset of languages in terms of their accuracy-efficiency Pareto front. As we ar…
A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing
Mark Anderson, Mathieu Dehouck, Carlos Gómez Rodríguez
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 accurac…