Step-by-Step CoT Verification
Labeling correctness of individual logic steps in complex reasoning chains.
Quality & Precision Benchmarks
STEP ACCURACY
99.4%
VERIFICATION DEPTH
Full Chain
Dataset Taxonomy & Output Structure
step_number
step_logic
is_step_valid
Specific Type Tasks & Applications
- • Math Problem Proofs
- • Logical Inference Verification
4-Stage Capture & Validation Process
1. Hardware Rig Setup
Calibration & zero-drift test
Calibration & zero-drift test
2. Field Execution
50Hz operator task capture
50Hz operator task capture
3. 3-Tier QA Audit
Sub-millisecond verification
Sub-millisecond verification
4. Secure Delivery
HDF5/Parquet cloud export
HDF5/Parquet cloud export
What Is Right vs What Is Wrong
| COMMON COMPETITOR ERRORS (WRONG) | BLUE PROJECTS GROUND TRUTH (RIGHT) |
|---|---|
| FAIL: Evaluating only final answer | PASS: Validating every intermediate logic step |
| FAIL: Ignoring subtle math fallacies | PASS: Pinpointing exact step-level reasoning errors |
Files & Telemetry Data Example (Python `h5py`)
import h5py
import numpy as np
# Load Blue Projects Type Dataset
with h5py.File('step-by-step-cot-verification_episode_001.h5', 'r') as f:
joint_data = np.array(f['observations/qpos'])
print("Loaded joint data shape:", joint_data.shape)
Network Footprint of Blue Projects
Blue Projects operates a dedicated 1,200 sq ft capture studio in Davanagere, Karnataka, India, paired with pan-India field operations. All datasets are captured in-house under strict MSME, GeM, and GDPR/DPDP compliant protocols.
Why Blue Projects for Step-by-Step CoT Verification?
Request a free matched 10-episode sample batch formatted to your exact hardware or policy model requirements.
Request Free Sample Batch →