RobertNLP at the IWPT 2021 Shared Task: Simple Enhanced UD Parsing for 17 Languages

Stefan Grünewald, Frederik Tobias Oertel, Annemarie Friedrich


Abstract
This paper presents our multilingual dependency parsing system as used in the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies. Our system consists of an unfactorized biaffine classifier that operates directly on fine-tuned XLM-R embeddings and generates enhanced UD graphs by predicting the best dependency label (or absence of a dependency) for each pair of tokens. To avoid sparsity issues resulting from lexicalized dependency labels, we replace lexical items in relations with placeholders at training and prediction time, later retrieving them from the parse via a hybrid rule-based/machine-learning system. In addition, we utilize model ensembling at prediction time. Our system achieves high parsing accuracy on the blind test data, ranking 3rd out of 9 with an average ELAS F1 score of 86.97.
Anthology ID:
2021.iwpt-1.21
Volume:
Proceedings of the 17th International Conference on Parsing Technologies and the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies (IWPT 2021)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP | IWPT
SIG:
SIGPARSE
Publisher:
Association for Computational Linguistics
Note:
Pages:
196–203
Language:
URL:
https://aclanthology.org/2021.iwpt-1.21
DOI:
10.18653/v1/2021.iwpt-1.21
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.iwpt-1.21.pdf