Parsing is an important process of Natural Language Processing (NLP) and Computational Linguistics which is used to understand the syntax and semantics of a natural language sentences confined to the grammar. Parser is a computational system which processes input sentence according to the productions of the grammar, and builds one or more constituent structures which conform to the grammar. The...

Nparse is a shallow probabilistic unification-based parser for N-best list resorting and the finding of simple grammatical phrases. It is data-driven and robust, allowing both domainspecific and unrestricted-language training. We believe it can be an interesting alternative for use in a synthesis or recognition front end. This parser has been trained for Swedish on a fine-grained set of grammat...

We investigate a number of approaches to generating Stanford Dependencies, a widely used semantically-oriented dependency representation. We examine algorithms specifically designed for dependency parsing (Nivre, Nivre Eager, Covington, Eisner, and RelEx) as well as dependencies extracted from constituent parse trees created by phrase structure parsers (Charniak, Charniak-Johnson, Bikel, Berkel...

one of the chief discussions within the phrase structure theory is the analysis of the projection level of modifiers of different grammatical categories. this study provides an analysis of the noun phrase structure in persian, considering the projection levels of the post-modifiers. the study is within the framework of the extended standard theory (est) and, in particular, x-bar syntax. data an...

We present a new discriminative reordering model for statistical machine translation. The model employs a standard data-driven dependency parser to predict reorderings based on syntactic information. This is made possible through the introduction of a reordering structure, which is a word alignment structure where the target word order is transposed onto the source sentence as a path. The appro...

Two new parsing algorithms for context-free phrase structure grammars are presented which perform a bounded amount of processing per word per analysis path, independently of sentence length. They are thus capable of parsing in real-time in a parallel implementation which forks processors in response to non-determinis-tic choice points. 0. INTRODUCTION The work reported here grew out of our atte...

For some time there has been interest in the idea of parsing as deduction. Here we present a grammat i cal tbrmalism, 'Axiomatic G r a m m a r ' , which is based upon a small number of linguistically motivated ax-toms and deduction rules. Each axiom or rule combines a 'category ' with a string of words to form a further category. This contrasts with the usual 'trees t ructure ' approach to synt...

This paper presents a comparative evaluation of several state-of-the-art English parsers based on different frameworks. Our approach is to measure the impact of each parser when it is used as a component of an information extraction system that performs protein-protein interaction (PPI) identification in biomedical papers. We evaluate eight parsers (based on dependency parsing, phrase structure...

We propose two general and robust methods for enriching resources annotated in the Frame Semantic paradigm with syntactic dependency graphs, which can provide useful additional information for applications such as semantic role labeling methods. One method incorporates information of a dependency parser, while the other one assumes the resource to be based on a treebank and uses dependency grap...

Freer-word-order languages such as German exhibit linguistic phenomena that present unique challenges to traditional CFG parsing. Such phenomena produce discontinuous constituents, which are not naturally modelled by projective phrase structure trees. In this paper, we examine topological field parsing, a shallow form of parsing which identifies the major sections of a sentence in relation to t...