Abstract
We investigate an aspect of the relationship between parsing and corpus-based methods in NLP that has received relatively little attention: coverage augmentation in rule-based parsers. In the specific task of determining grammatical relations (such as subjects and objects) in transcribed spoken language, we show that a combination of rule-based and corpus-based approaches, where a rule-based system is used as the teacher (or an automatic data annotator) to a corpus-based system, outperforms either system in isolation.- Anthology ID:
- W03-3019
- Volume:
- Proceedings of the Eighth International Conference on Parsing Technologies
- Month:
- April
- Year:
- 2003
- Address:
- Nancy, France
- Venue:
- IWPT
- SIG:
- SIGPARSE
- Publisher:
- Note:
- Pages:
- Language:
- URL:
- https://aclanthology.org/W03-3019
- DOI:
- Cite (ACL):
- Kenji Sagae and Alon Lavie. 2003. Combining Rule-based and Data-driven Techniques for Grammatical Relation Extraction in Spoken Language. In Proceedings of the Eighth International Conference on Parsing Technologies, Nancy, France.
- Cite (Informal):
- Combining Rule-based and Data-driven Techniques for Grammatical Relation Extraction in Spoken Language (Sagae & Lavie, IWPT 2003)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W03-3019.pdf