Morphology vs. syntax in adjective class acquisition

Authors:
Gemma Boleda;Toni Badia;Sabine Schulte im Walde
Affiliations:
Pompeu Fabra University, Barcelona;Pompeu Fabra University, Barcelona;Saarland University, Saarbrücken
Venue:
DeepLA '05 Proceedings of the ACL-SIGLEX Workshop on Deep Lexical Acquisition
Year:
2005

Citing 8
Cited 2

C4.5: programs for machine learning

C4.5: programs for machine learning
Assessing agreement on classification tasks: the kappa statistic

Computational Linguistics
An Applied Ontological Semantic Microtheory of Adjective Meaning for Natural Language Processing

Machine Translation
Automatic verb classification based on statistical distributions of argument structure

Computational Linguistics
Towards the automatic identification of adjectival scales: clustering adjectives according to meaning

ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Inducing German semantic verb classes from purely syntactic subcategorisation information

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Clustering polysemic subcategorization frame distributions semantically

ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Acquisition of semantic classes for adjectives from distributional evidence

COLING '04 Proceedings of the 20th international conference on Computational Linguistics

Prenominal modifier ordering via multiple sequence alignment

HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
A flexible approach to class-based ordering of prenominal modifiers

Empirical methods in natural language generation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper discusses the role of morphological and syntactic information in the automatic acquisition of semantic classes for Catalan adjectives, using decision trees as a tool for exploratory data analysis. We show that a simple mapping from the derivational type to the semantic class achieves 70.1% accuracy; syntactic function reaches a slightly higher accuracy of 73.5%. Although the accuracy scores are quite similar with the two resulting classifications, the kinds of mistakes are qualitatively very different. Morphology can be used as a baseline classification, and syntax can be used as a clue when there are mismatches between morphology and semantics.