From Contracts in Structured English to CL Specifications

In this paper we present a framework to analyze conflicts of contracts written in structured English. A contract that has manually been rewritten in a structured English is automatically translated into a formal language using the Grammatical Framework (GF). In particular we use the contract language CL as a target formal language for this translation. In our framework CL specifications could then be input into the tool CLAN to detect the presence of conflicts (whether there are contradictory obligations, permissions, and prohibitions. We also use GF to get a version in (restricted) English of CL formulae. We discuss the implementation of such a framework.Comment: In Proceedings FLACOS 2011, arXiv:1109.239

An intelligent contract editor

Architects have computer tools that complement their specialist knowledge, as do engineers. Notaries, however, do not. This is in spite of the work that has been done in formally modelling contracts, the basic work of notaries being contract drafting. We are currently working on a solution aimed at aiding and complementing notaries’ expertise. This will take the form of adding in to MS Word, the document processing program of choice of local notaries. Some of the functionality envisioned includes cross-referencing with the laws of Malta, automatically identifying parties involved in a clause, tracking contract changes and conflict detection.peer-reviewe

Predictive Contracting

This Article examines how contract drafters can use data on contract outcomes to inform contract design. Building on recent developments in contract data collection and analysis, the Article proposes “predictive contracting,” a new method of contracting in which contract drafters can design contracts using a technology system that helps predict the connections between contract terms and outcomes. Predictive contracting will be powered by machine learning and draw on contract data obtained from integrated contract management systems, natural language processing, and computable contracts. The Article makes both theoretical and practical contributions to the contracts literature. On a theoretical level, predictive contracting can lead to greater customization, increased innovation, more complete contract design, more effective balancing of front-end and back-end costs, better risk assessment and allocation, and more accurate term pricing for negotiation. On a practical level, predictive contracting has the potential to significantly alter the role of transactional lawyers by providing them with access to previously unavailable information on the statistical connections between contract terms and outcomes. In addition to these theoretical and practical contributions, the Article also anticipates and addresses limitations and risks of predictive contracting, including technical constraints, concerns regarding data privacy and confidentiality, the regulation of the unauthorized practice of law and the potential for exacerbating information inequality