FCV data-use paper corpus (6 configs)

.gitattributes

@@ -62,3 +62,4 @@ documents/all.jsonl filter=lfs diff=lfs merge=lfs -text
 sources/all.jsonl filter=lfs diff=lfs merge=lfs -text
 extraction/train.jsonl filter=lfs diff=lfs merge=lfs -text
 sources/train.jsonl filter=lfs diff=lfs merge=lfs -text
+synthetic/train.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -48,6 +48,10 @@ configs:
   data_files:
   - split: train
     path: "synthetic/train.jsonl"
+- config_name: synthetic-relation
+  data_files:
+  - split: train
+    path: "synthetic-relation/train.jsonl"
 - config_name: sources
   data_files:
   - split: train
@@ -74,13 +78,24 @@ All splits are published verbatim exactly as used in the paper.
 | `extraction` | train: 5183, validation: 415, test: 1706 |
 | `relation` | train: 640, validation: 91, holdout: 21 |
 | `impact` | train: 604, validation: 151, holdout: 84 |
-| `synthetic` | train: 1794 |
+| `synthetic` | train: 17611 |
+| `synthetic-relation` | train: 976 |
 | `sources` | train: 5445 |
 
 ## Schemas
 
-- `extraction` / `synthetic` / `sources`: `{"input", "output": {"entities":
+- `synthetic` / `sources`: `{"input", "output": {"entities":
   {"named_data", "descriptive_data", "vague_data"}, "entity_descriptions"}}`.
+- `synthetic` merges all entity-extraction synthetic training data (flat-NER +
+  `json_structures` transformed to flat-NER) with a `source` column tagging
+  provenance (`ner_strict`, `positives_v14`, `step3_short_span`,
+  `structures_strict`, `approach_e_5000`, `old_training_synth`,
+  `old_data_synth`, `old_combined`, `manual_seeds`).
+- `synthetic-relation`: relation-format synthetic training data (`{"input",
+  "output": {"entities": {"named_data", "organization"}, "relations":
+  [{"<type>": {"head", "tail"}}]}, "_meta"}`) from
+  `relation_training_synthetic` and `relation_llm_generated`, with a `source`
+  column.
 - `extraction` rows carry a `meta` field tagging provenance: `FCV`
   (forced-displacement / FCV corpus) or `PRWP` (Policy Research Working Papers
   -- manually annotated + reviewed/validated). `train` = FCV (2,473) + PRWP