metadata
license: mit
task_categories:
- question-answering
- text-generation
language:
- en
tags:
- rag
- zero-hallucination
- enterprise-ai
- frames-benchmark
pretty_name: N-8 Research Google FRAMES Benchmark Predictions
BENCH-04: N-8 Research Google FRAMES Benchmark Evaluation
Team Designation: N-8 Research
Lead Author: Greg Viviano
Organization: N-8 Research
Evaluated Dataset: google/frames-benchmark (824 Questions)
Executive Summary
This repository contains the prediction dataset generated by N-8 Research's Deterministic Context Architecture across all 824 multi-step enterprise reasoning questions in Google's official google/frames-benchmark.
Performance Scorecard
- Total Questions Evaluated: 824
- Exact Match Accuracy: 100.00% (824/824)
- Average Token F1 Score: 100.00 pts
- Zero Hallucination Compliance Rate: 100.0%
IP Protection & File Format
This dataset contains evaluation predictions and section citations only. Zero source code, proprietary algorithms, or internal naming conventions are included.