Extraction and representation of facts from legal briefs

Abstract

In knowledge-based consultation systems, the quality of the advice rendered depends on the techniques employed to represent the domain knowledge, the explanation generating capabilities, and the control strategies utilized during the consultative advice stage. The ability to understand the problem is more crucial in providing effective consultation. In this work, the emphasis is on understanding and the consequent formulation of a plausible internal representation of legal briefs. The system developed, SIFTER, reads the given input text from a legal practitioner's point of view and retrieves from it those facts that are relevant to the particular type of case on hand. In other words, it uses the domain specific knowledge to identify the type of case and to yank out the necessary information pertaining to the case. The SIFTER generates a noun-phrase processed form of the input which contains pseudo names for the proper-nouns, dates and time-intervals. The verbs in the processed input are used to check whether the case specific events have occurred or not and then the appropriate fact-containing noun-phrases are used to instantiate the relevant legal variables and, hence, to construct an internal representation of the given problem which can then be readily used by the consultative advice stage of a problem solver or analyzer. The implementation has been done in LISP culling the required domain knowledge from the Industrial Dispute Act of India.