Learning to resolve natural language ambiguities: a unified approach
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
A Learning Approach to Shallow Parsing
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COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
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Shallow parsing using specialized hmms
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ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
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Learning to identify reduced passive verb phrases with a shallow parser
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The necessity of syntactic parsing for semantic role labeling
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Unsupervised evaluation of parser robustness
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Legal language and legal knowledge management applications
Semantic Processing of Legal Texts
Evolutionary Shallow Natural Language Parsing
Computational Intelligence
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Significant amount of work has been devoted recently to develop learning techniques that can be used to generate partial (shallow) analysis of natural language sentences rather than a full parse. In this work we set out to evaluate whether this direction is worthwhile by comparing a learned shallow parser to one of the best learned full parsers on tasks both can perform --- identifying phrases in sentences. We conclude that directly learning to perform these tasks as shallow parsers do is advantageous over full parsers both in terms of performance and robustness to new and lower quality texts.