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.
@article{arxiv.1406.2538,
title = {FrameNet CNL: a Knowledge Representation and Information Extraction Language},
author = {Guntis Barzdins},
journal= {arXiv preprint arXiv:1406.2538},
year = {2014}
}
Comments
CNL-2014 camera-ready version. The final publication is available at link.springer.com