Disambiguation of the neuter pronoun and its effect on pronominal coreference resolution

Authors:
Véronique Hoste;Iris Hendrickx;Walter Daelemans
Affiliations:
LT3 - Language and Translation Technology Team, University College Ghent, Ghent, Belgium;CNTS - Language Technology Group, University of Antwerp, Antwerp, Belgium;CNTS - Language Technology Group, University of Antwerp, Antwerp, Belgium
Venue:
TSD'07 Proceedings of the 10th international conference on Text, speech and dialogue
Year:
2007

Citing 9
Cited 1

An algorithm for pronominal anaphora resolution

Computational Linguistics
A trainable approach to coreference resolution for information extraction

A trainable approach to coreference resolution for information extraction
A machine learning approach to coreference resolution of noun phrases

Computational Linguistics - Special issue on computational anaphora resolution
Identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution

COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Coreference resolution using competition learning approach

ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Combining sample selection and error-driven pruning for machine learning of coreference rules

EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Memory-Based Language Processing (Studies in Natural Language Processing)

Memory-Based Language Processing (Studies in Natural Language Processing)
Identifying non-referential it: a machine learning approach incorporating linguistically motivated patterns

FeatureEng '05 Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing
Evaluating hybrid versus data-driven coreference resolution

DAARC'07 Proceedings of the 6th discourse anaphora and anaphor resolution conference on Anaphora: analysis, algorithms and applications

Automatic Recognition of the Function of Singular Neuter Pronouns in Texts and Spoken Data

DAARC '09 Proceedings of the 7th Discourse Anaphora and Anaphor Resolution Colloquium on Anaphora Processing and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Coreference resolution, determining the appropriate discourse referent for an anaphoric expression, is an essential but difficult task in natural language processing. It has been observed that an important source of errors in machine-learning based approaches to this task, is the wrong disambiguation of the third person singular neuter pronoun as either referential or non-referential. In this paper, we investigate whether a machine learning based approach can be successfully applied to the disambiguation of the neuter pronoun in Dutch and show a modest potential effect of this disambiguation on the results of a machine learning based coreference resolution system for Dutch.