Automatic Extraction of Reasoning Chains from Textual Reports

Many organizations possess large collections of textual reports that document how a problem is solved or analysed, e.g. medical patient records, industrial accident reports, lawsuit records and investigation reports. Effective use of expert knowledge contained in these reports may greatly increase productivity of the organization. In this article, we propose a method for automatic extraction of reasoning chains that contain information used by the author of a report to analyse the problem at hand. For this purpose, we developed a graph-based text representation that makes the relations between textual units explicit. This representation is acquired automatically from a report using natural language processing tools including syntactic and discourse parsers. When applied to aviation investigation reports, our method generates reasoning chains that reveal the connection between initial information about the aircraft incident and its causes.