Developing and Orchestrating a Portfolio of Natural Legal Language Processing and Document Curation Services

Abstract

We present a portfolio of natural legal language processing and document curation services currently under development in a collaborative European project. First, we give an overview of the project and the different use cases, while, in the main part of the article, we focus upon the 13 different processing services that are being deployed in different prototype applications using a flexible and scalable microservices architecture. Their orchestration is operationalised using a content and document curation workflow manager.

Fine-Grained Named Entity Recognition in Legal Documents

“…The third pilot is a compliance solution in the domain of labour law, where legal provisions, case law, administrative resolutions, and expert literature are interlinked, analysed, and compared to define legal strategies for legal practice. The LYNX services are developed for several European languages including English, Spanish and German [32]. Documents in the legal domain contain multiple references to NEs, especially NEs specific to the legal domain, i.e., jurisdictions, legal institutions, etc.…”

Evaluating Document Representations for Content-based Legal Literature Recommendations

“…The research presented in this article is funded by the German Federal Ministry of Education and Research (BMBF) through the project QURATOR [42] (Unternehmen Region, Wachstumskern, no. 03WKDA1A) and by the project LYNX [43], which has received funding from the EU's Horizon 2020 research and innovation program under grant agreement no. 780602.…”

Observations on Annotations

“…Between the development phase and the deployment phase of an LT-based solution, annotation formats can also be mixed. For example, in LYNX, all processing solutions make use of NIF (Rehm et al 2019) but during the development and training phase of the German Legal NER model we used the CONLL format which is a simple, tab-seperated value, i.e., non-XML-based inline annotation format (Leitner et al 2019(Leitner et al , 2020.…”