Data-oriented Parsing

Darwinised Data-Oriented Parsing - Statistical NLP with Added Sex and Death

We present the Darwinised DataOriented Parsing algorithm, an incremental, dy-namic form of Data-Oriented Parsing, in which exemplars are used as replicators, subject to a selection pressure towards gen-eralisability.

An improved joint model: POS tagging and dependency parsing

Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do the POS tagging task along with dependency parsing in a pipeline mode. Unfortunately, in pipel...

Iterated Data-oriented Parsing as a Model for Diachronic Syntax Msc in Logic

Data-Oriented Parsing with Discontinuous Constituents and Function Tags

Discontinuous Data-Oriented Parsing: A mildly context-sensitive all-fragments grammar

Recent advances in parsing technology have made treebank parsing with discontinuous constituents possible, with parser output of competitive quality (Kallmeyer and Maier, 2010). We apply Data-Oriented Parsing (DOP) to a grammar formalism that allows for discontinuous trees (LCFRS). Decisions during parsing are conditioned on all possible fragments, resulting in improved performance. Despite the...