# BenGER Platform: A Collaborative Web Platform for End-to-End Benchmarking of German Legal Tasks

arXiv: https://arxiv.org/abs/2604.13583 · HTML: https://mlsanity.com/paper/2604.13583/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning.
- Builds on 0 of its 7 references that are in the map.
- First posted on arXiv 15 Apr 2026.

## Placed in

- LLM reasoning / [Reasoning for agents, planning and code](https://mlsanity.com/lr/reasoning-for-agents-planning-and-code/)

## Built on by (most cited first, 2 of 2)

- [BenGER: Benchmarking LLM Systems on Subsumption-Based Legal Reasoning in German Law](https://mlsanity.com/paper/2605.28183/) (2026)
- [SoK: Grading Open-Text Legal Answers, from Law School Exams to Trustworthy Rubric Judges](https://mlsanity.com/paper/2610.19992/) (2026)

## Abstract (arXiv)

Evaluating large language models (LLMs) for legal reasoning requires workflows that span task design, expert annotation, model execution, and metric-based evaluation. In practice, these steps are split across platforms and scripts, limiting transparency, reproducibility, and participation by non-technical legal experts. We present the BenGER (Benchmark for German Law) framework, an open-source web platform that integrates task creation, collaborative annotation, configurable LLM runs, and evaluation with lexical, semantic, factual, and judge-based metrics. BenGER supports multi-organization projects with tenant isolation and role-based access control, and can optionally provide formative, reference-grounded feedback to annotators. We will demonstrate a live deployment showing end-to-end benchmark creation and analysis.