Datasets:
license: mit
language:
- tr
size_categories:
- 10K<n<100K
Turkish Pseudo-Reasoning Dataset
This project creates synthetic reasoning traces in Turkish for simple, fully verifiable tasks. Its goal is to provide a pseudo-reasoning dataset with 100% label accuracy, suitable for establishing a controlled reasoning baseline before experimenting with noisier, model-generated, or open-ended traces.
Topics
The current dataset covers:
- Addition
- Subtraction
- Multiplication, including signed numbers
- Turkish letter counting
- Unit conversion across volume, length, and mass units
Methodology
Each example is generated from deterministic task logic and rendered through varied Turkish question, reasoning, and answer templates. The traces explain intermediate operations such as carrying, borrowing, sign handling, character enumeration, and conversion equations. Turkish decimal notation, grammatical suffixes, unit abbreviations, zero values, and task-specific edge cases are handled explicitly.
Answers are calculated by code rather than produced by a language model. The generation script enforces unique prompts per task type, checks expected row counts, writes the dataset to Parquet, reads it back, and runs consistency checks on randomly sampled records. Conversion records additionally use deterministic equations and bounded decimal formatting.
Intended Use
The dataset is intended for supervised fine-tuning, evaluation, ablation studies, and baseline experiments involving Turkish reasoning traces.