Law, Logic and Technology Research Lab Logo

The Research Laboratory for Law, Logic and Technology (LLT Lab) conducts empirical research on argument and reasoning patterns in diverse samples of legal documents, creating the semantic data, training protocols, and software analytics needed to develop technology to assist legal reasoning.

Vaccine/Injury Compensation

  • Vaccine/Injury Project

    Goal: Developing technology to assist human review of arguments and reasoning about awarding compensation for vaccine-related injuries.

  • V/IP Corpus

    Product: Semantic data consisting of annotated judicial decisions, useful for developing automation through machine learning or rule-based programming.

  • V/IP Reasoning

    Product: Argument structures that are either generic to legal reasoning, or specific to policy-based reasoning under the vaccine statute.

Medical Malpractice Compensation

  • Medical Malpractice Project

    Goal: Developing technology to assist human review of arguments and reasoning about awarding compensation for medical malpractice claims.

  • MedMal Corpus

    Product: Semantic data consisting of annotated judicial decisions, useful for developing automation through machine learning or rule-based programming.

  • Medical Malpractice Reasoning

    Product: Argument structures that are either generic to legal reasoning, or specific to policy-based reasoning in medical malpractice cases.

Veterans Claims

  • Veterans Claims Project

    Goal: Developing technology to assist human review of arguments and reasoning about claims for veterans benefits.

  • VetClaim Corpus

    Product: Semantic data consisting of annotated administrative and judicial decisions, useful for developing automation through machine learning or rule-based programming.

  • Veterans Claims Reasoning

    Product: Argument structures that are either generic to legal reasoning, or specific to policy-based reasoning in medical malpractice cases.