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Document Automation Tool Study is Published

We are happy to announce that our survey about document automation tools for the legal domain has been published.

The survey evaluates 13 document automation tools in accordance with requirements, which were identified with respect to the legal domain.

Please find the result of our survey here.

We would like to sincerely thank the 13 vendors who participated in our study and granted us access to their tools for conducting the study.

 

 


Two SEBIS Paper were nominated for LexisNexis Best Paper Award

Two papers of SEBIS were nominated for the LexisNexis Best Paper Award at IRIS 2018.

The first paper is about Named Entity Recognition, Extraction, and Linking in German Legal Documents and was written by Ingo Glaser, Benrhard Waltl and Florian Matthes. Please look here for furhter information about this paper.

The second paper from Daniel Braun, Elena Scepankova, Patrick Holl, and Florian Matthes is titled Customer-Centered LegalTech: Automated Analysis of Standard Form Contracts.


Paper on automated extraction of semantic information from german legal documents is nominated for LexisNexis Best Paper Award

Accepted for LexisNexis Best Paper Award

 

Abstract

Based on a collaborative data science environment, and a large document corpus (> 130.000 documents from German tax law) we demonstrate the extraction of semantic information. This paper shows the potential of rule-based text analysis to automatically extract semantic information, such as the year of dispute in cases. Additionally, it demonstrates the extraction of legal definitions in laws and the usage of terms in a defining context. Based on an iterative and interdisciplinary process, involving legal experts, software engineers, and data scientists, to evaluate and continuously refine the model used for the computer-supported extraction.