A modular cascaded approach to complete parsing

Abstract

In this paper, we propose a modular cascaded approach to data driven dependency parsing. Each module or layer leading to the complete parse produces a linguistically valid partial parse. We do this by introducing an artificial root node in the dependency structure of a sentence and by catering to distinct dependency label sets that reflect the function of the set internal labels vis--vis a distinct and identifiable linguistic unit, at different layers. The linguistic unit in our approach is a clause. Output (partial parse) from each layer can be accessed independently. We applied this approach to Hindi, a morphologically rich free word order language using MST Parser. We did all our experiments on a part of Hyderabad Dependency Treebank. The final results show an increase of 1.42% in unlabeled attachment and 1.23% in labeled attachment accuracies over state-of-the-art data driven Hindi parser.