mlsanityData to 7 Oct 2026

The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task

arXiv 2107.01982 ↗First posted 5 Jul 2021cs.CLcited by 1

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Abstract (arXiv)

We describe the DCU-EPFL submission to the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies. The task involves parsing Enhanced UD graphs, which are an extension of the basic dependency trees designed to be more facilitative towards representing semantic structure. Evaluation is carried out on 29 treebanks in 17 languages and participants are required to parse the data from each language starting from raw strings. Our approach uses the Stanza pipeline to preprocess the text files, XLMRoBERTa to obtain contextualized token representations, and an edge-scoring and labeling model to predict the enhanced graph. Finally, we run a post-processing script to ensure all of our outputs are valid Enhanced UD graphs. Our system places 6th out of 9 participants with a coarse Enhanced Labeled Attachment Score (ELAS) of 83.57. We carry out additional post-deadline experiments which include using Trankit for pre-processing, XLM-RoBERTa-LARGE, treebank concatenation, and multitask learning between a basic and an enhanced dependency parser. All of these modifications improve our initial score and our final system has a coarse ELAS of 88.04.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 18 of its 31 references that are in the map. First posted on arXiv 5 Jul 2021.

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18 of 31 references.

References · 18

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6 more
  1. 2019Compositional Semantic Parsing Across Graphbankscited by 15
  2. 2020Efficient EUD Parsingcited by 8
  3. 2020Enhanced Universal Dependency Parsing with Second-Order Inference and Mixture of Training Datacited by 5
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  1. 2023Transformers as Graph-to-Graph Modelscited by 5