Datasetpublic

ClarusC64/structural-bottleneck-classification-v0.1

What this dataset does This dataset tests whether a model can detect structural bottlenecks. The task is simple: Given a scenario and a structural-bottleneck claim, predict whether the claim is supported. Core stability idea A structural bottleneck is a constraint that limits system performance regardless of improvements elsewhere. Typical bottlenecks include: single approval points single processing nodes unique dependencies centralized routing irreplaceable… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/structural-bottleneck-classification-v0.1.

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What this dataset does

This dataset tests whether a model can detect structural bottlenecks.

The task is simple:

Given a scenario and a structural-bottleneck claim, predict whether the claim is supported.

Core stability idea

A structural bottleneck is a constraint that limits system performance regardless of improvements elsewhere.

Typical bottlenecks include:

—single approval points
—single processing nodes
—unique dependencies
—centralized routing
—irreplaceable personnel
—constrained resources

Removing a bottleneck often increases system capacity more effectively than optimizing surrounding components.

Prediction target

Binary label:

—1 = a structural bottleneck is present
—0 = a structural bottleneck is not present

Row structure

Each row contains:

—scenario_id
—scenario_text
—claim
—label

Files

—data/train.csv
—data/test.csv
—scorer.py
—README.md

Evaluation

bash

python scorer.py --predictions predictions.csv --truth data/test.csv

Structural Note

This dataset is intentionally small.

Its purpose is to test whether a model can identify limiting constraints embedded in system structure rather than transient operational issues.

License

MIT