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

Gabriel Marzinotto (1, 2) , Johannes Heinecke (3) , Geraldine Damnati (2)

1 TALEP - Traitement Automatique du Langage Ecrit et Parlé
2 Orange Labs [Lannion]
3 FT R&D - France Télécom Recherche & Développement

This paper describes our recursive system for SemEval-2019 \textit{ 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 feature that reflects the decisions made in previous steps. Process continues until the terminal nodes are reached. We choose a standard neural tagger and we focused 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.

Mots clés: UCCA; Semantics

Domaines: Informatique et langage [cs.CL]

Gabriel Marzinotto, Johannes Heinecke, Geraldine Damnati. MaskParse@Deskin at SemEval-2019 Task 1: Cross-lingual UCCA Semantic Parsing using Recursive Masked Sequence Tagging. Proceedings of the Thirteenth International Workshop on Semantic Evaluation, Jun 2019, Minneapolis, United States. ⟨hal-02298429⟩