Datasets:

UnstableLlama
/

semancy

license: other
language:
  - en
pretty_name: Semancer
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train.parquet
      - split: test
        path: data/test.parquet

Semancer

Semancer is a philosophy fine-tune dataset encoding an original philosophical framework across epistemology, physics and metaphysics, philosophy of mind, ethics, and AI philosophy. The training goal is to teach a model to reason from within the framework, not merely recite positions.

Splits

train: 436 examples, approved seed examples plus generated training examples.
test: 116 held-out eval examples derived from type rotations and cross-topic collisions, with eval_origin retained for traceability.

Format

Each row contains:

topic: primary framework topic.
type: explanatory, application, or adversarial.
subtopic: specific angle.
connections: related framework topics.
eval_origin: empty for train rows, seed mutation origin for test rows.
split: train or test.
messages: OpenAI-style single-turn user/assistant messages.

JSONL copies are included beside the Parquet files for direct inspection and training pipelines that prefer JSONL.

Notes

No system prompts are included in the training data. The assistant responses are written to embed the reasoning style directly.