Abstract
This paper describes a methodology aimed at grouping Catalan verbs according to their syntactic behavior. Our goal is to acquire a small number of basic classes with a high level of accuracy, using minimal resources. Information on syntactic class, expensive and slow to compile by hand, is useful for any NLP task requiring specific lexical information. We show that it is possible to acquire this kind of information using only a POS-tagged corpus. We perform two clustering experiments. The first one aims at classifying verbs into transitive, intransitive and verbs alternating with a se-construction. Our system achieves an average 0.84 F-score, for a task with a 0.33 baseline. The second experiment aims at further distinguishing among pure intransitives and verbs bearing a prepositional object. The baseline for the task is 0.51 and the upperbound 0.98. The system achieves an average 0.88 F-score.
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Abbreviations
- inf:
-
infinitive
- fut:
-
future tense
- OBJcli:
-
object clitic
- VASE:
-
Verbs alternating with se
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Acknowledgements
Many thanks to Toni Martí and Enric Vallduví and all the colleagues from the GLiCom for their useful comments. Special thanks are due to the Institut d’Estudis Catalans for lending us the research corpus, and to Nadjet Bouayad and Sebastian Padó for a critical revision of a previous version of this paper. Also thanks to Tom Rozario for language revision. This work is supported by the Departament d’Universitats, Recerca i Societat de la Informació (grants 2003FI-00867 and 2001FI-00582), and by the Fundación Caja Madrid.
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Mayol, L., Boleda, G. & Badia, T. Automatic acquisition of syntactic verb classes with basic resources. Lang Resources & Evaluation 39, 295–312 (2005). https://doi.org/10.1007/s10579-006-9000-x
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DOI: https://doi.org/10.1007/s10579-006-9000-x