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            <title>Proceedings of the Eighth International Conference on Parsing Technologies</title>
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    <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.</abstract>
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%0 Conference Proceedings
%T Combining Rule-based and Data-driven Techniques for Grammatical Relation Extraction in Spoken Language
%A Sagae, Kenji
%A Lavie, Alon
%S Proceedings of the Eighth International Conference on Parsing Technologies
%D 2003
%8 April
%C Nancy, France
%F sagae-lavie-2003-combining
%X 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.
%U https://aclanthology.org/W03-3019

Markdown (Informal)

[Combining Rule-based and Data-driven Techniques for Grammatical Relation Extraction in Spoken Language](https://aclanthology.org/W03-3019) (Sagae & Lavie, IWPT 2003)

• Combining Rule-based and Data-driven Techniques for Grammatical Relation Extraction in Spoken Language (Sagae & Lavie, IWPT 2003)

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.