Neural Networks for Multi-Word Expression Detection
Natalia Klyueva, Antoine Doucet, Milan Straka · 2017
In this paper we describe the MUMULS system that participated to the 2017 shared task on automatic identification of verbal multiword expressions (VMWEs).The MUMULS system was implemented using a supervised approach based on recurrent neural networks using the open source library TensorFlow.The model was trained on a data set containing annotated VMWEs as well as morphological and syntactic information.The MU-MULS system performed the identification of VMWEs in 15 languages, it was one of few systems that could categorize VMWEs type in nearly all languages.