OSU CHGCG at SemEval-2016 task 9: Chinese semantic dependency parsing with Generalized Categorial Grammar

Abstract

This paper introduces our Chinese semantic dependency parsing system for Task 9 of SemEval 2016. Our system has two components: a parser trained using the Berkeley Grammar Trainer on the Penn Chinese Treebank reannotated in a Generalized Categorial Grammar, and a multinomial logistic regression classifier. We first parse the data with the automatic parser to obtain predicate-argument dependencies and then we use the classifier to predict the semantic dependency labels for the predicate-argument dependency relations extracted. Although our parser is not trained directly on the task training data, our system yields the best performance for the non-local dependency recovery for the news data and comparable overall results.