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Contratto – A Method for Transforming Legal Contracts into Formal Specifications

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Book cover Research Challenges in Information Science (RCIS 2022)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 446))

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Abstract

Legal contracts have been used for millennia to conduct business transactions world-wide. Such contracts are expressed in natural language, and usually come in written form. We are interested in producing formal specifications from such legal text that can be used to formally analyze contracts, also serve as launching pad for generating smart contracts, information systems that partially automate, monitor and control the execution of legal contracts. We have been developing a method for transforming legal contract documents into specifications, adopting a semantic approach where transformation is treated as a text classification, rather than a natural language processing problem. The method consists of five steps that (a) Identify domain terms in the contract and manually disambiguate them when necessary, in consultation with stakeholders; (b) Semantically annotate text identifying obligations, powers, contracting parties, assets and situations; (c) Identify relationships among the concepts mined in (b); (d) Generate a domain model based on the terms identified in (a), as well as parameters and local variables for the contract; (e) Generate expressions that formalize the conditions of obligations and powers using terms identified in earlier steps in a contract specification language. This paper presents the method through an illustrative example, also reports on a prototype implementation of an environment that supports the method.

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Notes

  1. 1.

    Specifications describe what a contract does without describing how; they have been used extensively in Computer Science for software, hardware, business processes etc.

  2. 2.

    eBNF stands for ‘extended Backus-Naur form’ and consists of a notation for specifying programming language grammars.

  3. 3.

    The full specification can be found at https://legal-analysis.economia.unitn.it:7500/.

  4. 4.

    Spacy is a free open-source library for Natural Language Processing implementing a neural network for pre-trained models for name entity recognition https://spacy.io/.

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Authors and Affiliations

  1. University of Trento, Via Sommarive 14, 38123, Povo, TN, Italy

    Michele Soavi, Nicola Zeni & Luisa Mich

  2. University of Ottawa, 800 King Edward Ave., Ottawa, ON, K1N 6N5, Canada

    John Mylopoulos

Authors
  1. Michele Soavi
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  2. Nicola Zeni
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  3. John Mylopoulos
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  4. Luisa Mich
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Corresponding author

Correspondence to Michele Soavi .

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Editors and Affiliations

  1. University of Twente, Enschede, The Netherlands

    Renata Guizzardi

  2. University of Geneva, CUI, Carouge, Switzerland

    Jolita Ralyté

  3. Polytechnic University of Catalonia, Barcelona, Spain

    Xavier Franch

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Soavi, M., Zeni, N., Mylopoulos, J., Mich, L. (2022). Contratto – A Method for Transforming Legal Contracts into Formal Specifications. In: Guizzardi, R., Ralyté, J., Franch, X. (eds) Research Challenges in Information Science. RCIS 2022. Lecture Notes in Business Information Processing, vol 446. Springer, Cham. https://doi.org/10.1007/978-3-031-05760-1_20

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  • DOI: https://doi.org/10.1007/978-3-031-05760-1_20

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  • Online ISBN: 978-3-031-05760-1

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