| --- |
| license: apache-2.0 |
| language: |
| - en |
| tags: |
| - lean |
| - openai |
| - math |
| - clustering |
| - code |
| size_categories: |
| - 100K<n<1M |
| --- |
| # Dataset for OpenAI Lean Code grouping |
|
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| ### Published Lean code is clustered via combinatorial hierarchical clustering |
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| This is graph based ***combinatorial clustering*** not a statistical clustering in k-means clustering. |
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| This ***combinatorial clustering*** finds context and meaning among the data. |
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| ### Details |
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| - Total Files in the Github repo is **122141** |
| - Total Lean code lines **22358566** |
| - Total Lines taken for Clustering **5000000** |
| - Total Documents taken for Clustering **25391** |
| - Number of Code Line Clusters generated **248289** |
| - Number of File Clusters generated **3131** |
| - Total Lines in these clusters **3628607** |
| - Total Docs in these clusters **24738** |
| - % of lines which are clustered **72%** |
| - % of docs which are clustered **97%** |
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| ### How to understand the data |
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| - Finding similar contextual blocks allows the Lean code to be understood easily. Because the amount of generated code is so large that entire proofs can't be manually evaluated. |
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| - Finding similarity allows for easier code understanding because contextual comparison links both different part of code, files and domins easily. |
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| - Since this is LLM-generated Lean code for the mathematical proof, it will make tracing the reasoning or the method of LLM generation possible. |
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| - Full contextual clustering will be updated soon. |
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| ## Method |
| 1. The Lean code data is combined from all Lean code files in the GitHub repo. |
| 1. The code data is fed to the Graph AI based combinatorial clustering method directly. No change. |
| 1. The Graph AI compares the code lines via combinatorial clustering. |
| 1. Resulting clusters of code lines. |
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| ## Uses |
| * Can be used understand how the Lean code is generated by LLMs. |
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| ## Schema |
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| All files are **new line JSON** files. It could be loaded as **JSONL** |
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| 1. data_file.json - Base Data file |
| - doc_id - Unique ID for the file. |
| - data - data from lean code files. |
| - folder_name - folder name in which the Lean code file is located. |
| - domain_name - domain name from the folder name location. |
| - file_name - Lean code file name. |
| 2. line_data.json - Contains lines used for Clustering |
| - doc_id - Unique ID |
| - line_id - Unique ID |
| - line - Actual Lean Code line as it is. |
| 3. rows_clusters.json |
| - cluster_id - Unique ID denoting cluster. |
| - cluster - List of line_id that forms a conceptual cluster. |
| - confidence - Score of confidence showing how much these line_id are related. |
| 4. docs_clusters.json |
| - cluster_id - Unique ID denoting cluster |
| - cluster - List of doc_id that forms a conceptual cluster. |
| - confidence - Score of confidence showing how much these doc_id are related. |
