FW: Modeling Legal Text: A Tool Demonstration

Robin Gandhi

I’m forwarding this on behalf of Robin from UNO. As you know, UNO has been highly supportive of SPDX. The research Robin is discussing is outside of the scope of SPDX, but may be of interest to some.

On 7/6/17, 4:15 PM, "Robin Gandhi" <rgandhi@...> wrote:

Join the call:
Optional dial in number: 585-632-5623 PIN: 86451
**Best to join using a computer as I will using screen share for the demonstration.**

Meeting Time: Thurs, July 13, 8am PDT / 10 am CDT / 11am EDT / 15:00 UTC.

Hello all,
Please consider attending this conference call to provide feedback on a method to model legal text and its use for compliance analysis. The discussion will demonstrate associated tool support and discuss related model semantics.

Here is an abstract from a recent paper that our team authored:

Modular Norm Models: A Frame-Semantic Approach
Abstract— Norms in contractual agreements include claim-rights and corresponding duties. Analysis of norms expressed in voluminous legal text can benefit from the automation and traceability of logic-based models. Such norm models help reason about available rights and required duties based on the satisfiability of situations, a state-of-affair, in a given scenario. But model extraction from natural language needs subject matter expertise. Compliance reasoning in complex scenarios using large norm model networks is also difficult. We outline a novel method for modular norm model extraction and reasoning. For extraction, using the theory of frame-semantics we construct two foundational norm templates that cover Hohfeld’s concepts of claim-right and its jural correlative, duty. Template instantiations from legal text result in a re- peatable method for extraction of modular norm models. For reasoning, we introduce the notion of a super-situation. Super- situations contain other norm models. Compliance results from a modular norm are propagated to its containing super-situation, which in turn participates in other modular norms. This modularity allows on-demand incremental modeling and reasoning using simpler model primitives than previous approaches. We show our method on a variety of contractual statements in privacy and open source software domains.

Here is the Github repository with some demonstration links: