Professor Vern R. Walker, Karina Vazirova ’14 and Cass Sanford (to graduate December 2014), all members of Hofstra Law’s Law, Logic and Technology Research Laboratory (LLT Lab), published a paper in the Proceedings of the First Workshop on Argumentation Mining, pp. 1-10 (Association for Computational Linguistics 2014).
Professor Walker presented the paper at the Workshop on June 26, 2014, at the Annual Meeting of the Association for Computational Linguistics, in Baltimore, Maryland.
The paper addresses the problem that automated argumentation mining requires an adequate type system or annotation scheme for classifying the patterns of argument that succeed or fail in a corpus of legal documents.
Moreover, there must be a reliable and accurate method for classifying the arguments found in natural language legal documents. Without an adequate and operational type system, we are unlikely to reach consensus on argument corpora that can function as a gold standard.
This paper reports the preliminary results of research to annotate a sample of representative judicial decisions for the reasoning of the fact-finder.
The decisions report whether the evidence adduced by the petitioner adequately supports the claim that a medical theory causally links some type of vaccine with various types of injuries or adverse medical conditions.
The paper summarizes and discusses some patterns of reasoning that are being found in the LLT Lab, using examples from the corpus.
The pattern types and examples presented in the paper demonstrate the difficulty of developing a type or annotation system for characterizing the logically important patterns of reasoning.