Knowledge Acquisition of Predicate Argument Structures from Technical Texts Using Machine learning: The System ASIUM

摘要

In this paper, we describe the Machine Learning system, ASIUM~1, which learns Subcaterorization Frames of verbs and ontologies from the syntactic parsing of technical texts in natural language. The restrictions of selection in the subcategorization frames are filled by the ontology's concepts. Applications requiring such knowledge are crucial and numerous. The most direct applications are semantic control of texts and syntactic parsing disambiguation.