MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging

Gabriel Marzinotto, Johannes Heinecke, Géraldine Damnati


Abstract
This paper describes our recursive system for SemEval-2019 Task 1: Cross-lingual Semantic Parsing with UCCA. Each recursive step consists of two parts. We first perform semantic parsing using a sequence tagger to estimate the probabilities of the UCCA categories in the sentence. Then, we apply a decoding policy which interprets these probabilities and builds the graph nodes. Parsing is done recursively, we perform a first inference on the sentence to extract the main scenes and links and then we recursively apply our model on the sentence using a masking features that reflects the decisions made in previous steps. Process continues until the terminal nodes are reached. We chose a standard neural tagger and we focus on our recursive parsing strategy and on the cross lingual transfer problem to develop a robust model for the French language, using only few training samples
Anthology ID:
S19-2015
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
107–112
Language:
URL:
https://aclanthology.org/S19-2015
DOI:
10.18653/v1/S19-2015
Bibkey:
Cite (ACL):
Gabriel Marzinotto, Johannes Heinecke, and Géraldine Damnati. 2019. MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 107–112, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging (Marzinotto et al., SemEval 2019)
Copy Citation:
PDF:
https://aclanthology.org/S19-2015.pdf
Data
BioFrameNet