For the LLT Lab’s Medical Malpractice (“MedMal”) Project, the Lab helps to make legal knowledge operational and computational by annotating a sample of medical malpractice decisions in the United States, and by identifying the logic structures found in these decisions. There are many objectives for this data project, but the major ones include:

  • To comparatively investigate the rule systems and evidence assessment patterns in medical malpractice cases in the United States and Italy.
  • To develop protocols for using the LLT Lab’s linguistic and logical framework to investigate legal decisions in two different legal systems involving two different natural languages.
  • To develop annotated texts to serve as data in developing and testing software analytics for automating argument mining.
  • To develop an adequate theory of heuristics for mining logical structures in legal texts that report fact-finding and evidence assessment.
  • To develop operational protocols for creating valid and reliable data from raw legal texts in this area of law.
  • To develop a library of annotated legal texts for both legal and non-legal online education.
  • To create methods for training legal decision-makers and legal practitioners, as well as researchers and students, in the use of logic skills.
  • To demonstrate the feasibility of a scalable, team approach in applying the linguistic and logical framework to legal decisions generally.
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