Abstract
We describe a mechanism for automatically estimating frequencies of verb subcategorization frames in a large corpus. A tagged corpus is first partially parsed to identify noun phrases and then a regular grammar is used to estimate the appropriate subcategorization frame for each verb token in the corpus. In an experiment involving the identification of six fixed subcategorization frames, our current system showed more than 80% accuracy. In addition, a new statistical method enables the system to learn patterns of errors based on a set of training samples and substantially improves the accuracy of the frequency estimation.- Anthology ID:
- 1993.iwpt-1.24
- Volume:
- Proceedings of the Third International Workshop on Parsing Technologies
- Month:
- August 10-13
- Year:
- 1993
- Address:
- Tilburg, Netherlands and Durbuy, Belgium
- Editors:
- Harry Bunt, Robert Berwick, Ken Church, Aravind Joshi, Ronald Kaplan, Martin Kay, Bernard Lang, Makoto Nagao, Anton Nijholt, Mark Steedman, Henry Thompson, Masaru Tomita, K. Vijay-Shanker, Yorick Wilks, Kent Wittenburg
- Venue:
- IWPT
- SIG:
- SIGPARSE
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 309–318
- Language:
- URL:
- https://aclanthology.org/1993.iwpt-1.24
- DOI:
- Cite (ACL):
- Akira Ushioda, David A. Evans, Ted Gibson, and Alex Waibel. 1993. Frequency Estimation of Verb Subcategorization Frames Based on Syntactic and Multidimensional Statistical Analysis. In Proceedings of the Third International Workshop on Parsing Technologies, pages 309–318, Tilburg, Netherlands and Durbuy, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Frequency Estimation of Verb Subcategorization Frames Based on Syntactic and Multidimensional Statistical Analysis (Ushioda et al., IWPT 1993)
- PDF:
- https://preview.aclanthology.org/corrections-2024-05/1993.iwpt-1.24.pdf