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Overview of the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies

What it is about

The overview introduces the task of parsing raw text into enhanced UD graphs, where a word may have several heads, graphs may contain cycles, and empty nodes may appear, for 17 languages. Training data came from UD 2.5, with enhancements added by the organisers where a treebank lacked them. The main metric is ELAS, the labelled F1 over enhanced edges with full subtypes; EULAS ignores subtypes. The coarse scores average over languages, and the qualitative scores ignore enhancement types that a treebank does not annotate. The validity rules (one or more roots, every node reachable, no self-loops) caught several teams by surprise. The best English system reached ELAS 88.94, and the authors conclude that enhanced parsing is harder than basic parsing but the drop is small for most systems.

Ideas

For Mova

The enhanced layer is derived in Mova, so ELAS and EULAS on EWT dev measure the derivation as well as the parser. The ideas touch 24. Coordination and subordination (propagated conjuncts) and 29-ellipsis-word-order-information-structure.md (empty nodes and gapping). Decide on dev; EWT test runs once per release.

Topics: Universal Dependencies · Treebanks

Cite

The paper itself, not this card. BibTeX from the library's record of the work. DOI 10.18653/v1/2020.iwpt-1.16

@inproceedings{bouma2020overview,
  title = {{Overview of the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies}},
  author = {Bouma, Gosse and Seddah, Djamé and Zeman, Daniel},
  booktitle = {Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies},
  year = {2020},
  doi = {10.18653/v1/2020.iwpt-1.16},
  url = {https://doi.org/10.18653/v1/2020.iwpt-1.16}
}

References

25 references, 11 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

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