Initial Explorations of CCG Supertagging for Universal Dependency Parsing
Burak Kerim Akkus | Heval Azizoglu | Ruket Cakici
Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
In this paper we describe the system by METU team for universal dependency parsing of multilingual text. We use a neural network-based dependency parser that has a greedy transition approach to dependency parsing. CCG supertags contain rich structural information that proves useful in certain NLP tasks. We experiment with CCG supertags as additional features in our experiments. The neural network parser is trained together with dependencies and simplified CCG tags as well as other features provided.