Skimming stories in real time: an experiment in integrated understanding.
Skimming stories in real time: an experiment in integrated understanding.
Computational Linguistics
Scruffy text understanding: design and implementation of 'tolerant' understanders
ACL '82 Proceedings of the 20th annual meeting on Association for Computational Linguistics
Integrated processing produces robust understanding
Computational Linguistics
Analyzing telegraphic messages
HLT '89 Proceedings of the workshop on Speech and Natural Language
Communications of the ACM
Techniques for automatically correcting words in text
ACM Computing Surveys (CSUR)
Categorizing Unknown Words: A Decision Tree-Based Misspelling Identifier
AI '99 Proceedings of the 12th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
Categorizing unknown words: using decision trees to identify names and misspellings
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Responding to semantically ill-formed input
ANLC '88 Proceedings of the second conference on Applied natural language processing
ANLC '88 Proceedings of the second conference on Applied natural language processing
Compansion: From research prototype to practical integration
Natural Language Engineering
How to detect grammatical errors in a text without parsing it
EACL '87 Proceedings of the third conference on European chapter of the Association for Computational Linguistics
An environment for acquiring semantic information
ACL '87 Proceedings of the 25th annual meeting on Association for Computational Linguistics
Towards a more user-friendly correction
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
GramCheck: a grammar and style checker
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Contribution of a category hierarchy to the robustness of syntactic parsing.
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
VOX: an extensible natural language processor
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
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Most large text-understanding systems have been designed under the assumption that the input text will be in reasonably "neat" form (for example, newspaper stories and other edited texts). However, a great deal of natural language text (for example, memos, messages, rough drafts, conversation transcripts, etc.) have features that differ significantly from "neat" texts, posing special problems for readers, such as misspelled words, missing words, poor syntactic construction, unclear or ambiguous interpretation, missing crucial punctuation, etc. Our solution to these problems is to make use of expectations, based both on knowledge of surface English and on world knowledge of the situation being described. These syntactic and semantic expectations can be used to figure out unknown words from context, constrain the possible word senses of words with multiple meanings (ambiguity), fill in missing words (ellipsis), and resolve referents (anaphora). This method of using expectations to aid the understanding of "scruffy" texts has been incorporated into a working computer program called NOMAD, which understands scruffy texts in the domain of Navy ship-to-shore messages.