language: en

Confluent Preorder Parsing

CS-TR-95-03
HO, Kei Shiu Edward and CHAN, Lai Wan
Department of Computer Science The Chinese University of Hong Kong
Shatin, N.T., Hong Kong
email : ho052@cs.cuhk.hk and lwchan@cs.cuhk.hk KEYWORDS: Neural Networks, Connectionist Syntactic Parsing, RAAM, Holistic Transformation, Confluent Preorder Parser, Linearization of a Hierarchical Parse Tree, Parsing Erroneous Sentences, Syntactic Disambiguation

Abstract In this paper, syntactic parsing is discussed in the context of connectionism. A new model - the Confluent Preorder Parser (CPP), is proposed which exemplifies the holistic parsing paradigm. Holistic parsing has the advantage that little assumption has to be made concerning the detailed parsing algorithm, which is often unknown or debatable, especially when human language understanding is concerned. In the CPP, syntactic parsing is achieved by transforming in a oneshot manner, from the connectionist representation of the sentence to the connectionist representation of the preorder traversal of its parse tree, instead of the parse tree itself. As revealed by the simulation experiments, generalization performance is excellent (as high as 90%). Besides, the CPP is also capable of parsing erroneous sentences and resolving syntactic ambiguities. A systematic study is conducted to explore the range of factors which can affect the effectiveness of it. This error-recovery capability is especially useful in natural language processing when incomplete or even ungrammatical sentences are to be dealt with.

1. Introduction