Programming in Prolog
Introduction: toward a theory of reading and understanding
Understanding language understanding
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
ELIZA—a computer program for the study of natural language communication between man and machine
Communications of the ACM
A question-answering interpretation of resolution refutation
A question-answering interpretation of resolution refutation
QUE: an expert system explanation facility that answers "why not" types of questions
Journal of Computing Sciences in Colleges
Deep Read: a reading comprehension system
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Reading comprehension programs in a statistical-language-processing class
ANLP/NAACL-ReadingComp '00 Proceedings of the 2000 ANLP/NAACL Workshop on Reading comprehension tests as evaluation for computer-based language understanding sytems - Volume 6
Story understanding through multi-representation model construction
HLT-NAACL-TEXTMEANING '03 Proceedings of the HLT-NAACL 2003 workshop on Text meaning - Volume 9
Binding skolem clauses in theorem prover resolution for automated hypothetical question answering
CIMMACS'06 Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics
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Document undestanding offer interesting alternative to the kinds of special-purpose, carefully constructed evaluations that have driven many recent research in language understanding. It involves the process of reading a specific text document and answer the questions about it, to demonstrate one's understanding of the document by returning exact phrase answers. This research aims to implement proposed logical formalisms by expanding the notion of answer literal for understanding task such as question answering. This paper modify the skolem arguments to broaden the notion of answer literal to all context of question that conducted, including universal quantifier and ground term. There are two symbols, fn represents the quantified variable names, while gn represents ground term variable names. The expanding of the notion of answer literal enables the document to be tested by all context of question, including universal quantified and ground term variables. Both answers link to the concept of capability that is considered in this experiment.