6533b7dcfe1ef96bd1271de7

RESEARCH PRODUCT

FrameNet CNL: A Knowledge Representation and Information Extraction Language

Guntis Barzdins

subject

Information retrievalParsingKnowledge representation and reasoningbusiness.industryComputer scienceAgency (philosophy)computer.software_genreParaphraseInformation extractionArtificial intelligenceSource textFrameNetbusinesscomputerNatural language processingNatural language

description

The paper presents a FrameNet-based information extraction and knowledge representation framework, called FrameNet-CNL. The framework is used on natural language documents and represents the extracted knowledge in a tailor-made Frame-ontology from which unambiguous FrameNet-CNL paraphrase text can be generated automatically in multiple languages. This approach brings together the fields of information extraction and CNL, because a source text can be considered belonging to FrameNet-CNL, if information extraction parser produces the correct knowledge representation as a result. We describe a state-of-the-art information extraction parser used by a national news agency and speculate that FrameNet-CNL eventually could shape the natural language subset used for writing the newswire articles.

yearjournalcountryeditionlanguage
2014-01-01
https://doi.org/10.1007/978-3-319-10223-8_9