An efficient context-free parsing algorithm
Communications of the ACM
Using Combinatory Categorial Grammar to Extract Biomedical Information
IEEE Intelligent Systems
Grammatical specification of domain ontologies
Data & Knowledge Engineering - NLDB2002
Speech and Language Processing (2nd Edition)
Speech and Language Processing (2nd Edition)
Conceptual Indexing of Text Using Ontologies and Lexical Resources
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Ontological constitutions for classes and properties
ICCS'06 Proceedings of the 14th international conference on Conceptual Structures: inspiration and Application
Conceptual Indexing of Text Using Ontologies and Lexical Resources
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Extracting conceptual feature structures from text
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
A semantics-based approach to retrieving biomedical information
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
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We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora.