Learning the countability of English nouns from corpus data

Authors:
Timothy Baldwin;Francis Bond
Affiliations:
Stanford University, Stanford, CA;Nippon Telegraph and Telephone Corporation, Kyoto, Japan
Venue:
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Year:
2003

Citing 8
Cited 13

Learning methods to combine linguistic indicators: improving aspectual classification and revealing linguistic insights

Computational Linguistics
Applied morphological processing of English

Natural Language Engineering
Morphological cues for lexical semantics

ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Countability and number in Japanese to English machine translation

COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Using an ontology to determine English countability

COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Transformation-based learning in the fast lane

NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Introduction to the CoNLL-2000 shared task: chunking

ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
A plethora of methods for learning English countability

EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing

Web-based models for natural language processing

ACM Transactions on Speech and Language Processing (TSLP)
A plethora of methods for learning English countability

EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Detecting errors in English article usage by non-native speakers

Natural Language Engineering
Acquiring the meaning of discourse markers

ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Inferring parts of speech for lexical mappings via the Cyc KB

COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Reinforcing English countability prediction with one countability per discourse property

COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
A Method for Reinforcing Noun Countability Prediction

IEICE - Transactions on Information and Systems
Automatic acquisition of grammatical types for nouns

NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
Bootstrapping deep lexical resources: resources for courses

DeepLA '05 Proceedings of the ACL-SIGLEX Workshop on Deep Lexical Acquisition
Chart mining-based lexical acquisition with precision grammars

HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Automatic detection of non-deverbal event nouns for quick lexicon production

COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Detecting article errors based on the mass count distinction

IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Informing determiner and preposition error correction with word clusters

Proceedings of the Seventh Workshop on Building Educational Applications Using NLP

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a method for learning the countability preferences of English nouns from raw text corpora. The method maps the corpus-attested lexico-syntactic properties of each noun onto a feature vector, and uses a suite of memory-based classifiers to predict membership in 4 countability classes. We were able to assign countability to English nouns with a precision of 94.6%.