  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.
