docs: align card with published condition-5 configs (ur/zh/es)

Aligns the dataset card with the published condition-5 data:

- Raw/pre-cleanup caveat note for the `condition-5-*` configs
- Config table: correct ur numbers (4,088/381), add zh (4,052/381) and es (4,032/329)
- New Condition 5 schema section (7 cols = conditions 1-2 + `idx`)
- Condition 5 row in the Experimental Conditions table
- Condition 5 entries in Dataset Description, Available Configs, Usage, Technical Details, and Limitations

Frontmatter and condition-1/2 configs untouched.

README.md

@@ -921,7 +921,7 @@ Prior work ([Aryabumi et al., 2024 -- "To Code or Not to Code"](https://arxiv.or
 
 ## Dataset Description
 
-This dataset provides filtered, quality-controlled Python source code in multiple configurations: the original English, three keyword-swapped variants (Chinese, Spanish, Urdu), a blended native+transpiled mix, and strictly native Chinese code. The source data is drawn from [bigcode/the-stack-dedup](https://huggingface.co/datasets/bigcode/the-stack-dedup) (Python subset), filtered for quality using the following criteria:
+This dataset provides filtered, quality-controlled Python source code in multiple configurations: the original English, three keyword-swapped variants (Chinese, Spanish, Urdu), a blended native+transpiled mix, strictly native Chinese code, and a model-translated set in which an LLM translates the full source (identifiers, strings, and comments, not just keywords). The source data is drawn from [bigcode/the-stack-dedup](https://huggingface.co/datasets/bigcode/the-stack-dedup) (Python subset), filtered for quality using the following criteria:
 
 - AST-valid Python only (must parse without errors)
 - Permissive licenses only (MIT, Apache-2.0, BSD, etc.)
@@ -934,7 +934,7 @@ Keyword-swapped variants are produced using [Legesher](https://github.com/legesh
 
 ## Available Configs
 
-Conditions 1--2 are available in three current Phase 3 sizes: `-103k` full corpora, `-20k` random subsets sampled from the corresponding `-103k` config with seed 42, and `-5k` compact subsets. Phase 2 `-32k` configs are still available with the `phase-2-the-stack-v1-*` prefix.
+Conditions 1--2 are available in three current Phase 3 sizes: `-103k` full corpora, `-20k` random subsets sampled from the corresponding `-103k` config with seed 42, and `-5k` compact subsets. Phase 2 `-32k` configs are still available with the `phase-2-the-stack-v1-*` prefix. Condition 5 (`condition-5-*-c4ai-aya-expanse-32b`) is the model-translated set — currently `5k` only, and raw/pre-cleanup (see the note above).
 
 | Config                    | Condition   | Language | Description                                      | Train  | Val    |
 | ------------------------- | ----------- | -------- | ------------------------------------------------ | ------ | ------ |
@@ -952,7 +952,9 @@ Conditions 1--2 are available in three current Phase 3 sizes: `-103k` full corpo
 | `condition-2-ur-5k`       | 2           | Urdu     | Compact 5k subset                                | 4,500  | 500    |
 | `condition-3-zh-5k`       | 3           | Chinese  | Blended: native Chinese code + transpiled Python | 4,500  | 500    |
 | `condition-4-zh-5k`       | 4           | Chinese  | Strictly native Chinese code                     | 6,553  | 729    |
-| `condition-5-ur-5k-c4ai-aya-expanse-32b` | 5 | Urdu | Model-translated Urdu condition                  | 4,024  | 447    |
+| `condition-5-ur-5k-c4ai-aya-expanse-32b` | 5 | Urdu    | Model-translated (full LLM translation via Cohere Aya) — raw, pre-cleanup | 4,088 | 381 |
+| `condition-5-zh-5k-c4ai-aya-expanse-32b` | 5 | Chinese | Model-translated (full LLM translation via Cohere Aya) — raw, pre-cleanup | 4,052 | 381 |
+| `condition-5-es-5k-c4ai-aya-expanse-32b` | 5 | Spanish | Model-translated (full LLM translation via Cohere Aya) — raw, pre-cleanup | 4,032 | 329 |
 
 ## Schema
 
@@ -969,6 +971,22 @@ Used by: `condition-1-en-*`, `condition-2-zh-*`, `condition-2-es-*`, `condition-
 | `license`     | string | SPDX license identifier for the source file.                                                                                                         |
 | `token_count` | int64  | Token count computed using the CohereLabs/tiny-aya-base tokenizer.                                                                                   |
 
+### Condition 5
+
+Used by: `condition-5-ur-5k-c4ai-aya-expanse-32b`, `condition-5-zh-5k-c4ai-aya-expanse-32b`, `condition-5-es-5k-c4ai-aya-expanse-32b`
+
+Condition 5 uses the conditions 1--2 schema plus an `idx` column. `code` is the full LLM-translated source (identifiers, strings, comments, and keywords); `code_en` is the English original. These configs are raw model output — see the note at the top of this card.
+
+| Column        | Type   | Description                                                                           |
+| ------------- | ------ | ------------------------------------------------------------------------------------- |
+| `code`        | string | Model-translated Python source (full LLM translation via Cohere Aya).                 |
+| `code_en`     | string | Original English Python source code.                                                  |
+| `language`    | string | ISO 639-1 language code: `ur`, `zh`, or `es`.                                         |
+| `file_path`   | string | Original file path in The Stack Dedup.                                                |
+| `license`     | string | SPDX license identifier for the source file.                                          |
+| `idx`         | int64  | Source row index into `condition-1-en-5k`. Enables row-level joins across conditions.  |
+| `token_count` | int64  | Token count computed using the CohereLabs/tiny-aya-base tokenizer.                     |
+
 ### Condition 3
 
 Used by: `condition-3-zh-5k`
@@ -1015,6 +1033,7 @@ The Language Decoded experiment uses a ladder of conditions to isolate the mecha
 | Condition 2 | Keyword-swapped code | Tests whether the _language_ of keywords matters for the reasoning benefit                |
 | Condition 3 | Mixed native sources | Tests whether diverse native-language code adds value beyond keyword swapping             |
 | Condition 4 | Strictly native code | Tests whether code authored by native speakers carries unique signal beyond transpilation |
+| Condition 5 | Model-translated code | Tests whether full LLM translation (identifiers, strings, comments -- not just keywords) changes the reasoning benefit, relative to Condition 2's keyword-only swap |
 
 ### The Experimental Ladder
 
@@ -1051,6 +1070,11 @@ ds = load_dataset("legesher/language-decoded-data", "condition-3-zh-5k")
 # Load strictly native code (condition 4)
 ds = load_dataset("legesher/language-decoded-data", "condition-4-zh-5k")
 
+# Load model-translated code (condition 5 -- raw, pre-cleanup)
+ds = load_dataset("legesher/language-decoded-data", "condition-5-ur-5k-c4ai-aya-expanse-32b")
+ds = load_dataset("legesher/language-decoded-data", "condition-5-zh-5k-c4ai-aya-expanse-32b")
+ds = load_dataset("legesher/language-decoded-data", "condition-5-es-5k-c4ai-aya-expanse-32b")
+
 # Access splits
 train = ds["train"]
 val = ds["validation"]
@@ -1067,6 +1091,7 @@ native_only = train.filter(lambda x: x["source_type"] == "native")
 | Transpilation tool     | [Legesher](https://github.com/legesher/legesher) v0.7.3 (legesher-core, legesher-i18n)                             |
 | Tokenizer              | CohereLabs/tiny-aya-base                                                                                           |
 | Base model             | [CohereLabs/tiny-aya-base](https://huggingface.co/CohereLabs/tiny-aya-base) (3.35B params)                         |
+| Condition 5 translation model | Cohere `c4ai-aya-expanse-32b` (Aya Expanse 32B, via the Cohere API) |
 | Train/validation split | 90% / 10% (seed 42)                                                                                                |
 | File format            | Parquet (snappy compression)                                                                                       |
 | Filtering criteria     | AST-valid, permissive licenses, 10--1000 lines, min 21 GitHub stars, no autogenerated files, SHA-256 deduplication |
@@ -1078,6 +1103,7 @@ native_only = train.filter(lambda x: x["source_type"] == "native")
 - **Token count variation**: Transpiled code may have different token counts than the English original due to multi-byte characters (especially for Chinese and Urdu), even though the code structure is identical.
 - **Single programming language**: Currently limited to Python. Results may not generalize to other programming languages.
 - **Condition 4 scope**: Native Chinese code is limited to publicly available sources (The Stack, Wenyan, Program-in-Chinese, Qi, Mulan) and may not represent the full spectrum of Chinese-language programming.
+- **Condition 5 is raw model output**: The `condition-5-*` configs contain prompt-leakage contamination -- translator-model preamble text, JSON wrappers, and explanation commentary leaked into string literals and identifier names, in AST-valid and AST-invalid rows alike. Cleaned configs will be published separately. See the note at the top of this card.
 
 ## Citation