Data Oriented Parsing

In Data Oriented Parsing (DOP), an annotated corpus is used as a stochastic grammar. An input string is parsed by combining subtrees from the corpus. As a consequence, one parse …...

Excellent results have been reported for Data- Oriented Parsing (DOP) of natural language texts (Bod, 1993c). Unfortunately, existing algorithms are both computationally intensive and difficult to implement. Previous algorithms are …...

We develop a Data-Oriented Parsing (DOP) model based on the syntactic representations of Lexical- Functional Grammar (LFG). We start by sum- marizing the original DOP model for tree represen- tations …...

Common wisdom has it that the bias of stochastic grammars in favor of shorter derivations of a sentence is harmful and should be redressed. We show that the common wisdom …...

We aim at finding the minimal set of fragments which achieves maximal parse accuracy in Data Oriented Parsing. Expe- riments with the Penn Wall Street Journal treebank show that counts …...

This paper introduces a new application of boost- ing for parse reranking. Several parsers have been proposed that utilize the all-subtrees representa- tion (e.g., tree kernel and data oriented parsing). …...

The Data-Oriented Translation (DOT) model – originally proposed in (Poutsma, 1998, 2003) and based on Data-Oriented Parsing (DOP) (e.g. (Bod, Scha, & Sima’an, 2003)) – is best described as a …...

Tree substitution grammars (TSGs) are a com- pelling alternative to context-free grammars for modelling syntax. However, many popu- lar techniques for estimating weighted TSGs (under the moniker of Data Oriented …...

We present a novel approach to Data-Oriented Parsing (DOP). Like other DOP models, our parser utilizes syntactic fragments of arbitrary size from a treebank to analyze new sentences, but, crucially, …...