Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Semi-automatic acquisition of conceptual structure from technical texts
International Journal of Man-Machine Studies
Mixed-strategy matching in conceptual networks
Methodologies for intelligent systems, 5
Planning in Conceptual Networks
ICCI '91 Proceedings of the International Conference on Computing and Information: Advances in Computing and Information
Explanation-based Learning Helps Acquire Knowledge from Natural Language Texts
ISMIS '91 Proceedings of the 6th International Symposium on Methodologies for Intelligent Systems
Computational Linguistics
Language As a Cognitive Process: Syntax
Language As a Cognitive Process: Syntax
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The TANKA project seeks to build a model of a technical domain by semi-automatically processing unedited English text that describes this domain. Each sentence is parsed and conceptual elements are extracted from the parse. Concepts are derived from the Case structure of a sentence, and added to a conceptual network that represents knowledge about the domain. The DIPETT parser has a particularly broad coverage of English syntax; its newest version can also process sentence fragments. The HAIKU subsystem is responsible for user-assisted semantic interpretation. It contains a Case Analyzer module that extracts phrases marking concepts from the parse and uses its past processing experience to derive the most likely Case realizations of each with almost no a priori semantic knowledge. The user must validate these selections. A key issue in our research is minimizing the number of interactions with the user by intelligently generating the alternatives offered.