A Data-Oriented Parsing Model for HPSG

HPSG–DOP: data–oriented parsing with HPSG

Introduction to Data-Oriented Parsing

We present HPSG–DOP, a method for automatically extracting a Stochas-tic Lexicalized Tree Grammar (SLTG) from a HPSG source grammar and a given corpus. 1 Processing of a SLTG is performed by a specialized fast parser. The approach has been tested on a large English grammar and has been shown to achieve additional performance increase compared to parsing with a highly tuned HPSG parser. Our appr...

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...

Probabilistic Models for Disambiguation of an HPSG-Based Chart Generator

We describe probabilistic models for a chart generator based on HPSG. Within the research field of parsing with lexicalized grammars such as HPSG, recent developments have achieved efficient estimation of probabilistic models and high-speed parsing guided by probabilistic models. The focus of this paper is to show that two essential techniques – model estimation on packed parse forests and beam...

Clp Based Hpsg Parsing

We describe a system for principle based parsing of HPSG employing constraint logic programming techniques. Typed features structures are implemented as constraints on PROLOG variables and are instantiated in a lazy fashion. Grammar principles as well as relational constraints are stated in a declarative way by means of conditional constraints on feature structures. The procedural interpretatio...