Cross-Lingual SRL Based upon Universal Dependencies
Ondřej Pražák
and
Miloslav Konopík
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017 (2017)
BibTex
|
PDF
Research topics
Semantic analysis
Abstract
In this paper, we introduce a cross-lingual Semantic Role Labeling (SRL) system
with language independent features based upon Universal Dependencies. We
propose two methods to convert SRL annotations from monolingual dependency
trees into universal dependency trees. Our SRL system is based upon
cross-lingual features derived from universal dependency trees and a supervised
learning that utilizes a maximum entropy classifier. We design experiments to
verify whether the Universal Dependencies are suitable for the cross-lingual
SRL. The results are very promising and they open new interesting research
paths for the future.