Semantic Annotation of Legal Contracts with ContrattoA

Author:

Soavi MicheleORCID,Zeni NicolaORCID,Mylopoulos John,Mich LuisaORCID

Abstract

The aim of the research is to semi-automate the process of generating formal specifications from legal contracts in natural language text form. Towards this end, the paper presents a tool, named ContrattoA, that semi-automatically conducts semantic annotation of legal contract text using an ontology for legal contracts. ContrattoA was developed through two iterations where lexical patterns were defined for legal concepts and their effectiveness was evaluated with experiments. The first iteration was based on a handful of sample contracts and resulted in defining lexical patterns for recognizing concepts in the ontology; these were evaluated with an empirical study where one group of subjects was asked to annotate legal text manually, while a second group edited the annotations generated by ContrattoA. The second iteration focused on the lexical patterns for the core contract concepts of obligation and power where results of the first iteration were mixed. On the basis of an extended set of sample contracts, new lexical patterns were derived and those were shown to substantially improve the performance of ContrattoA, nearing in quality the performance of experts. The experiments suggest that good quality annotations can be generated for a broad range of contracts with minor refinements to the lexical patterns.

Publisher

MDPI AG

Subject

Computer Networks and Communications,Human-Computer Interaction,Communication

Reference38 articles.

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1. A hybrid model utilizing transfer learning for legal citation linking;International Journal of Information Technology;2023-06

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