Ontology Based Text Understanding and Text Generation for Legal Technology Applications

Abstract

The paper presents a software solution for text understanding and text generation, which finds new opportunities for being applied in the area of Legal Tech. The solution belongs to the problem domain of natural language processing and covers the gaps in legal documentation comparative analysis and generation. Modern trends in information technology implementation in Legal Tech are overviewed and summarized to generate the recommendations of text understanding and text generation solutions, practical implementation and use. Based on the attributes extracted from legal text documents, a subject area ontological model is formed to describe, organize and present the relationships between the facts extracted from documents, for example, normative legal acts, their individual clauses, subparagraphs, specific named entities, facts and their relationships. Experimental research was carried out to extract entities including facts and attributes from a set of administrative regulations which contains 537 documents. The proposed solution demonstrates the benefits of knowledge based text understanding and text generation in Legal Tech.