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A NOVEL MODEL FOR TIMED EVENT EXTRACTION AND TEMPORAL REASONING IN LEGAL TEXT DOCUMENTS

Information Retrieval is in a nascent stage to provide any type of information queried by naive user. Question Answering System is one such successful area of Information retrieval. Legal Documents (case law, statute or transactional document) are increasing day by day with the new applications (Mobile transactions, Medical Diagnosis reports, law cases etc.) in the world. Documentation of various Business and Human Resource (HR) applications involve Legal documents. Analysis and temporal reasoning of such documents is a demanding area of research. In this paper we build a novel model for timed event extraction and temporal reasoning in legal text documents. This paper mainly works on “how one can do further reasoning with the extracted temporal information”. Exploring temporal information in legal text documents is an important task to support legal practitioner lawyer, in order to determine temporal based context decisions. Legal documents are available in different natural languages; hence it uses NLP System for pre-processing steps, Temporal constraint structure for temporal expressions, associated tagger, Post-Processor with a knowledge-based sub system helps in discovering implicit information. The resultant information resolves temporal expressions and deals with issues such as granularity, vagueness, and a reasoning mechanism which models the temporal constraint satisfaction network .