Informatics Report Series



Related Pages

Report (by Number) Index
Report (by Date) Index
Author Index
Institute Index

Title:Object Extraction and Question-Parsing using CCG
Authors: Stephen Clark ; Mark Steedman ; James Curran
Date: 2004
Publication Title:Proceedings of EMNLP 2004 (Conference on Empirical Methods in Natural Language Processing)
Publication Type:Conference Paper Publication Status:Published
Page Nos:111-118
Accurate dependency recovery has recently been reported for a number of wide-coverage statistical parsers using Combinatory Categorial Grammar (CCG). However, overall figures give no indication of a parser s performance on specific constructions, nor how suitable a parser is for specific applications. In this paper we give a detailed evaluation of a CCG parser on object extraction dependencies found in WSJ text. We also show how the parser can be used to parse questions for Question Answering. The accuracy of the original parser on questions is very poor, and we propose a novel technique for porting the parser to a new domain, by creating new labelled data at the lexical category level only. Using a supertagger to assign categories to words, trained on the new data, leads to a dramatic increase in question parsing accuracy.
Links To Paper
ACL Anthology (publisher)
Personal web page
Bibtex format
author = { Stephen Clark and Mark Steedman and James Curran },
title = {Object Extraction and Question-Parsing using CCG},
book title = {Proceedings of EMNLP 2004 (Conference on Empirical Methods in Natural Language Processing)},
publisher = {ACL},
year = 2004,
pages = {111-118},
url = {},

Home : Publications : Report 

Please mail <> with any changes or corrections.
Unless explicitly stated otherwise, all material is copyright The University of Edinburgh