Add dataset card explaining interpreter corpus + teacher caches

README.md

@@ -0,0 +1,90 @@
+---
+pretty_name: "LUT-SLM — Interpreter Corpus & Teacher Caches"
+license: other
+language:
+  - en
+task_categories:
+  - text-generation
+  - text-classification
+size_categories:
+  - 10K<n<100K
+tags:
+  - color-grading
+  - lut
+  - instruction-following
+  - routing
+  - refusal
+  - captioning
+  - synthetic
+---
+
+# LUT-SLM — Interpreter Corpus & Teacher Caches
+
+Training data and teacher-LLM caches for the **Stage-1 interpreter/router** of the LUT-SLM project
+(the model itself: **[`ericrcwu/LUT_SLM_interpreter`](https://huggingface.co/ericrcwu/LUT_SLM_interpreter)**).
+It supplies the *(free-text request → route + attribute spec)* supervision that teaches the router to
+choose **`grade`** / **`clarify`** / **`refuse`** for a photo-editing instruction.
+
+This is a **companion** to the source corpus
+**[`ericrcwu/LUT_SLM`](https://huggingface.co/datasets/ericrcwu/LUT_SLM)**: the grade rows here are
+teacher captions of that corpus's real, measured LUTs, and every row is stamped with its source LUT's
+leakage-safe `split_unit_id` so no near-duplicate straddles the train/eval boundary.
+
+## Files
+
+```
+data/
+├── interpreter/
+│   ├── interpreter_rows.jsonl           # UNIFIED interpreter corpus (the training target)
+│   └── interpreter_corpus_manifest.json # counts + provenance for the unified corpus
+└── active_sft/
+    ├── caption_rows.jsonl               # teacher captions of real LUTs -> grade rows
+    ├── caption_cache.jsonl              # raw teacher caption generations (resume cache)
+    ├── caption_gen_manifest.json        # caption run manifest
+    ├── route_supplement_rows.jsonl      # clarify + out_of_gamut supplement rows
+    ├── route_supplement_cache.jsonl     # raw teacher generations for the supplement
+    └── route_supplement_manifest.json   # supplement run manifest
+```
+
+## The unified corpus (`interpreter_rows.jsonl`)
+
+`interpreter_corpus_version: interpreter_v1` — built by `build_interpreter_corpus.py`, which joins the
+grade captions, the refuse corpus, and the clarify supplement, stamping each with the source LUT's
+`split_unit_id`.
+
+| | |
+|---|---|
+| Total rows | **15,077** |
+| By route | grade **13,805** · refuse **772** · clarify **500** |
+| Refuse kinds | out_of_scope **272** · out_of_gamut **500** |
+| Source families | caption **13,805** · unsupported_teacher **1,272** |
+| Distinct split units | 2,869 |
+| Caption styles (×2,761 each) | `concept`, `literal`, `metaphor`, `mood`, `slang` |
+
+The 13,805 grade rows are 2,761 real LUTs each captioned in **5 stylistic registers** (concept /
+literal / metaphor / mood / slang), so the router sees the same underlying edit phrased many ways. The
+refuse rows reuse the `unsupported` teacher corpus (edits a global LUT cannot express); the clarify /
+`out_of_gamut` rows are an additive supplement validated by absence-of-direction cues.
+
+## How captions are made
+
+Grade captions are **synthetic and behavior-grounded**: a teacher LLM (Claude) is shown a real LUT's
+*measured* behavior (the CIEDE2000/Lab delta vector from the source corpus) and writes a natural
+request that describes it, cross-checked so the phrasing matches the measured direction. See the
+[`LUT_SLM`](https://huggingface.co/datasets/ericrcwu/LUT_SLM) card for the full measurement +
+teacher/judge methodology. The `*_cache.jsonl` files are the raw resume-safe generation logs behind
+the curated `*_rows.jsonl`.
+
+## Intended use
+
+- Train / evaluate the Stage-1 interpreter as a **router** (grade / clarify / refuse) over free-text
+  color-editing requests.
+- Study instruction phrasing vs. routing robustness across the 5 caption styles.
+
+## Licensing & provenance
+
+`license: other`. These rows are teacher-LLM text derived from the mixed-provenance
+[`LUT_SLM`](https://huggingface.co/datasets/ericrcwu/LUT_SLM) corpus, some of whose sources are
+**personal-use / non-redistribution** (see that dataset's licensing section). This repository makes
+**no license claim** over the underlying content. Research use; verify source terms before any
+redistribution or commercial use.