# `logo-lab/dlte` per-config schema reference

Two configs:

- **`manifests`**: lightweight metadata as one parquet stream with a unified
  `(record_type, record_json)` schema.
- **`lake`**: full table content (parents + fragments + distractors) with
  typed columns + provenance keys.

## `manifests` config

Single split (`train`), 109,336 records.

| Column | Type | Notes |
|---|---|---|
| `record_type` | `string` | one of: `parent`, `fragment`, `lake_table`, `split_assignment`, `query_task`, `ckan_distractor`, `fragmentation_config`, `gt_validation` |
| `record_json` | `string` | JSON-encoded record content (variable schema per `record_type`) |

### `record_type` counts

| record_type | rows | source |
|---|---|---|
| `lake_table` | 47,772 | `manifests/lake_manifest.jsonl` |
| `ckan_distractor` | 36,740 | `manifests/ckan_distractor_ids.txt` (one row per id) |
| `fragment` | 16,548 | `manifests/fragments_manifest.jsonl` |
| `query_task` | 5,516 | `ground_truth/query_tasks.jsonl` |
| `parent` | 1,379 | `manifests/parents_filtered.jsonl` |
| `split_assignment` | 1,379 | `manifests/splits.json` (one row per (parent_id, split)) |
| `fragmentation_config` | 1 | `config/fragmentation.json` |
| `gt_validation` | 1 | `ground_truth/gt_validation.json` |

### Record schemas (after `json.loads(record_json)`)

- **`parent`**: `{parent_id, dataset, csv_path, csv_stem, table_id_in_embeddings, n_rows, n_cols, key_col, key_col_idx, key_uniqueness, key_non_null_ratio, key_is_text}`
- **`fragment`**: `{table_id, parent_id, split, role, fragment_type, noise_tier, replicate_id, csv_path, n_rows, n_cols, key_col_fragment, key_col_parent}`
- **`lake_table`**: `{table_id, source, parent_id, fragment_type, noise_tier, replicate_id, split, csv_path, n_rows, n_cols}` — the full lake of 47,772 (= 11,032 targets + 36,740 distractors)
- **`split_assignment`**: `{parent_id, split}` (split ∈ {train, dev, test})
- **`query_task`**: `{query_table_id, parent_id, split, noise_tier, replicate_id, relevant: [{table_id, relation}, ...]}`
- **`ckan_distractor`**: `{distractor_id}`
- **`fragmentation_config`**: full config blob (tiers, noise specs)
- **`gt_validation`**: validation ground truth blob

## `lake` config

Single split (`train`), **54,667 rows** (= 1,379 parents + 16,548 fragments [5,516 query_seed + 5,516 target_union + 5,516 target_join] + 36,740 distractors). Sharded by byte budget (~1.5 GB raw per shard) so each parquet column page stays under the INT32 limit.

| Column | Type | Notes |
|---|---|---|
| `table_id` | `string` | unique within the lake |
| `kind` | `string` | `parent_tabfact` / `parent_wtq` / `target_union` / `target_join` / `query_seed` / `distractor` |
| `parent_id` | `string` | empty for distractors |
| `parent_source` | `string` | `tabfact` / `wtq` / empty (distractor) |
| `noise_tier` | `int32` | 0/1/2/3 for fragments; -1 for parents/distractors |
| `fragment_type` | `string` | `seed` / `union` / `join` / empty |
| `split` | `string` | `train` / `dev` / `test` / empty (distractors are unsplit) |
| `csv_text` | `large_string` | raw CSV content of the table |
| `n_rows` | `int32` | row count (excluding header) |
| `n_cols` | `int32` | column count |

### Counts by `kind`

| kind | count | provenance |
|---|---|---|
| `parent_tabfact` | 989 | TabFact (Chen et al., ICLR 2020) |
| `parent_wtq` | 390 | WikiTableQuestions (Pasupat & Liang, ACL 2015) |
| `target_union` | 5,516 | derived: row-blocks removed from parents |
| `target_join` | 5,516 | derived: column-blocks removed from parents |
| `query_seed` | 5,516 | derived: parent minus removed rows + columns |
| `distractor` | 36,740 | LakeBench-Srinivas Zenodo CKAN Subset pool |
| **Total** | **54,667** | — |

Of these, **47,772 = `target_union` + `target_join` + `distractor`** is the *retrieval lake* the pipeline searches over. The other 6,895 (1,379 parents + 5,516 query seeds) are released alongside as pipeline I/O.

## Cross-config keys

- `manifests.lake_table.record_json["table_id"]` ↔ `lake.table_id` for `kind ∈ {target_union, target_join, distractor}`
- `manifests.parent.record_json["parent_id"]` ↔ `lake.parent_id` (and matches `lake.table_id` for `kind ∈ {parent_*}`)
- `manifests.split_assignment.record_json["parent_id"]` ↔ `lake.parent_id` for parent rows

Stage-2 calibrated thresholds for the (Stage-1 backbone, Stage-2 column model) pairs evaluated in the paper are not included in this release; they are deterministic given the dev split and reproducible from the operator spec in the paper appendix.