Conceptual Knowledge Acquisition Using Automatically Generated Large−Scale Semantic Networks (This is not the final version)
Pia−Ramona Wojtinnek‚ Brian Harrington‚ Sebastian Rudolph and Stephen Pulman
We present a method for automatically creating large-scale semantic networks from natural language text, based on deep semantic analysis. We provide a robust and scalable implementation, and sketch various ways in which the representation may be deployed for conceptual knowledge acquisition. A translation to RDF establishes interoperability with a wide range of standardised tools, and bridges the gap to the field of semantic technologies.