Experiments in Inductive Chart Parsing

James Cussens; Stephen Pulman

Experiments in Inductive Chart Parsing

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution

Abstract

We use Inductive Logic Programming (ILP) within a chart-parsing framework for grammar learning. Given an existing grammar G, together with some sentences which G can not parse, we use ILP to find the ``missing'' grammar rules or lexical items. Our aim is to exploit the inductive capabilities of chart parsing, i.e. the ability to efficiently determine what is needed for a parse. For each unparsable sentence, we find actual edges and *needed edges*: those which are needed to allow a parse. The former are used as background knowledge for the ILP algorithm (P-Progol) and the latter are used as examples for the ILP algorithm. We demonstrate our approach with a number of experiments using context-free grammars and a feature grammar.

Original language	English
Title of host publication	Learning Language in Logic
Editors	James Cussens, Saso Dzeroski
Publisher	Springer
Volume	1925
Publication status	Published - 2000

Publication series

Name	LNAI
Publisher	Springer

Cite this

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title = "Experiments in Inductive Chart Parsing",

abstract = "We use Inductive Logic Programming (ILP) within a chart-parsing framework for grammar learning. Given an existing grammar G, together with some sentences which G can not parse, we use ILP to find the ``missing'' grammar rules or lexical items. Our aim is to exploit the inductive capabilities of chart parsing, i.e. the ability to efficiently determine what is needed for a parse. For each unparsable sentence, we find actual edges and *needed edges*: those which are needed to allow a parse. The former are used as background knowledge for the ILP algorithm (P-Progol) and the latter are used as examples for the ILP algorithm. We demonstrate our approach with a number of experiments using context-free grammars and a feature grammar.",

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AU - Pulman, Stephen

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N2 - We use Inductive Logic Programming (ILP) within a chart-parsing framework for grammar learning. Given an existing grammar G, together with some sentences which G can not parse, we use ILP to find the ``missing'' grammar rules or lexical items. Our aim is to exploit the inductive capabilities of chart parsing, i.e. the ability to efficiently determine what is needed for a parse. For each unparsable sentence, we find actual edges and *needed edges*: those which are needed to allow a parse. The former are used as background knowledge for the ILP algorithm (P-Progol) and the latter are used as examples for the ILP algorithm. We demonstrate our approach with a number of experiments using context-free grammars and a feature grammar.

AB - We use Inductive Logic Programming (ILP) within a chart-parsing framework for grammar learning. Given an existing grammar G, together with some sentences which G can not parse, we use ILP to find the ``missing'' grammar rules or lexical items. Our aim is to exploit the inductive capabilities of chart parsing, i.e. the ability to efficiently determine what is needed for a parse. For each unparsable sentence, we find actual edges and *needed edges*: those which are needed to allow a parse. The former are used as background knowledge for the ILP algorithm (P-Progol) and the latter are used as examples for the ILP algorithm. We demonstrate our approach with a number of experiments using context-free grammars and a feature grammar.

M3 - Other chapter contribution

VL - 1925

T3 - LNAI

BT - Learning Language in Logic

A2 - Cussens, James

A2 - Dzeroski, Saso

PB - Springer

ER -