Abstract
Our submission for Task 1 ‘Cross-lingual Semantic Parsing with UCCA’ at SemEval-2018 is a feed-forward neural network that builds upon an existing state-of-the-art transition-based directed acyclic graph parser. We replace most of its features by deep contextualized word embeddings and introduce an approximation to represent non-terminal nodes in the graph as an aggregation of their terminal children. We further demonstrate how augmenting data using the baseline systems provides a consistent advantage in all open submission tracks. We submitted results to all open tracks (English, in- and out-of-domain, German in-domain and French in-domain, low-resource). Our system achieves competitive performance in all settings besides the French, where we did not augment the data. Post-evaluation experiments showed that data augmentation is especially crucial in this setting.- Anthology ID:
- S19-2016
- Volume:
- Proceedings of the 13th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2019
- Address:
- Minneapolis, Minnesota, USA
- Editors:
- Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 113–118
- Language:
- URL:
- https://aclanthology.org/S19-2016
- DOI:
- 10.18653/v1/S19-2016
- Cite (ACL):
- Tobias Pütz and Kevin Glocker. 2019. Tüpa at SemEval-2019 Task1: (Almost) feature-free Semantic Parsing. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 113–118, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
- Cite (Informal):
- Tüpa at SemEval-2019 Task1: (Almost) feature-free Semantic Parsing (Pütz & Glocker, SemEval 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/S19-2016.pdf