Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10M - 100M
License:
Update README.md
Browse files
README.md
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## How it was built
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### v0.1
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1. **Fast filter**: skip any document that doesn't contain obvious CLI indicators (`$`, `sudo`, `pip install`, `` ```bash ``, `root@`, etc.)
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2. **Score**: remaining docs are scored (0-34) across five signals, each with a per-match point value and a cap:
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3. **Dedup**: exact dedup across both datasets using xxhash64 on full text. Removed 1,168 duplicates.
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### v0.2
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The unfiltered subset is ~84-86% noise at lower score levels (5-12), which make up 93% of the data. The root cause: v0.1's scoring uses context-blind keyword matching
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v0.2 applies a three-stage structural filter over the unfiltered data:
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1. **Context-aware
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2. **Validation regex**: confirms a genuine structural terminal pattern exists
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3. **Weighted structural scoring** (`term_score_v2`): each pattern has a weight (1-3) and occurrences are capped. Documents need `term_score_v2 >= 3` to be kept.
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| Weight | Signal | Max |
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No indentation-based scoring. No context-blind command substring matching.
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**Result**: 3.8% of the unfiltered data survives
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## Schema
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## How it was built
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### v0.1 Unfiltered
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1. **Fast filter**: skip any document that doesn't contain obvious CLI indicators (`$`, `sudo`, `pip install`, `` ```bash ``, `root@`, etc.)
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2. **Score**: remaining docs are scored (0-34) across five signals, each with a per-match point value and a cap:
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3. **Dedup**: exact dedup across both datasets using xxhash64 on full text. Removed 1,168 duplicates.
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### v0.2 Clean
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The unfiltered subset is ~84-86% noise at lower score levels (5-12), which make up 93% of the data. The root cause: v0.1's scoring uses context-blind keyword matching, CLI command names like `find`, `make`, `cat` appear in normal English prose, bare `$` matches currency amounts, and indented Python/SQL code gets scored as terminal content.
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v0.2 applies a three-stage structural filter over the unfiltered data:
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1. **Context-aware**: instead of matching bare `$`, requires `$ sudo`, `$ git`, `$ docker`, etc. (dollar sign + space + known command). Eliminates ~87% of documents immediately.
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2. **Validation regex**: confirms a genuine structural terminal pattern exists, shell prompts followed by real commands, `user@host:~$` patterns, Python REPL `>>>`, tracebacks, `` ```bash `` code blocks, Unix file permission listings, man page headers, shebangs.
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3. **Weighted structural scoring** (`term_score_v2`): each pattern has a weight (1-3) and occurrences are capped. Documents need `term_score_v2 >= 3` to be kept.
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| Weight | Signal | Max |
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No indentation-based scoring. No context-blind command substring matching.
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**Result**: 3.8% of the unfiltered data survives, from 61.3M rows down to 2.33M rows. Quality jumps from ~15% to ~98% terminal/CLI content.
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## Schema
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