Robust processing of real-world natural-language texts
Text-based intelligent systems
An intelligent analyzer and understander of English
Communications of the ACM
Transition network grammars for natural language analysis
Communications of the ACM
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
Structural ambiguity and lexical relations
Computational Linguistics - Special issue on using large corpora: I
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Probabilistic top-down parsing and language modeling
Computational Linguistics
Robustness beyond shallowness: incremental deep parsing
Natural Language Engineering
Two principles of parse preference
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 3
A simple pattern-matching algorithm for recovering empty nodes and their antecedents
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Heuristics for broad-coverage natural language parsing
HLT '93 Proceedings of the workshop on Human Language Technology
Incremental parsing with the perceptron algorithm
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Non-projective dependency parsing using spanning tree algorithms
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
Using an incremental robust parser to automatically generate semantic UNL graphs
ROMAND '04 Proceedings of the 3rd Workshop on RObust Methods in Analysis of Natural Language Data
A classifier-based parser with linear run-time complexity
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
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Despite the popularity of stochastic parsers, symbolic parsing still has some advantages, but is not practical without an effective mechanism for selecting among alternative analyses. This paper describes the symbolic preference system of a hybrid parser that combines a shallow parser with an overlay parser that builds on the chunks. The hybrid currently equals or exceeds most stochastic parsers in speed and is approaching them in accuracy. The preference system is novel in using a simple, three-valued scoring method (-1, 0, or +1) for assigning preferences to constituents viewed in the context of their containing constituents. The approach addresses problems associated with earlier preference systems, and has considerably facilitated development. It is ultimately based on viewing preference scoring as an engineering mechanism, and only indirectly related to cognitive principles or corpus-based frequencies.