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FCV data-use paper corpus (6 configs)

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  1. README.md +7 -16
  2. extraction/train.jsonl +2 -2
README.md CHANGED
@@ -44,10 +44,6 @@ configs:
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  path: "impact/validation.jsonl"
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  - split: holdout
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  path: "impact/holdout.jsonl"
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- - config_name: synthetic
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- data_files:
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- - split: train
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- path: "synthetic/train.jsonl"
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  - config_name: synthetic-relation
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  data_files:
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  - split: train
@@ -75,31 +71,26 @@ All splits are published verbatim exactly as used in the paper.
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  | Config | Splits (records) |
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  |---|---|
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- | `extraction` | train: 5183, validation: 415, test: 1706 |
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  | `relation` | train: 640, validation: 91, holdout: 21 |
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  | `impact` | train: 604, validation: 151, holdout: 84 |
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- | `synthetic` | train: 17611 |
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  | `synthetic-relation` | train: 976 |
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  | `sources` | train: 5445 |
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  ## Schemas
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- - `synthetic` / `sources`: `{"input", "output": {"entities":
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  {"named_data", "descriptive_data", "vague_data"}, "entity_descriptions"}}`.
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- - `synthetic` merges all entity-extraction synthetic training data (flat-NER +
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- `json_structures` transformed to flat-NER) with a `source` column tagging
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- provenance (`ner_strict`, `positives_v14`, `step3_short_span`,
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- `structures_strict`, `approach_e_5000`, `old_training_synth`,
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- `old_data_synth`, `old_combined`, `manual_seeds`).
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  - `synthetic-relation`: relation-format synthetic training data (`{"input",
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  "output": {"entities": {"named_data", "organization"}, "relations":
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  [{"<type>": {"head", "tail"}}]}, "_meta"}`) from
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  `relation_training_synthetic` and `relation_llm_generated`, with a `source`
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  column.
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- - `extraction` rows carry a `meta` field tagging provenance: `FCV`
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- (forced-displacement / FCV corpus) or `PRWP` (Policy Research Working Papers
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- -- manually annotated + reviewed/validated). `train` = FCV (2,473) + PRWP
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- (2,710); `validation` and `test` are FCV-only.
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  - `relation`: `{"input", "output": {"entities": {"named_data",
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  "organization"}, "relations": [{"<type>": {"head", "tail"}}]}, "_meta"}`
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  with types `has_organization`, `used_by`, `has_acronym`, `has_timeframe`,
 
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  path: "impact/validation.jsonl"
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  - split: holdout
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  path: "impact/holdout.jsonl"
 
 
 
 
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  - config_name: synthetic-relation
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  data_files:
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  - split: train
 
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  | Config | Splits (records) |
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  |---|---|
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+ | `extraction` | train: 22794, validation: 415, test: 1706 |
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  | `relation` | train: 640, validation: 91, holdout: 21 |
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  | `impact` | train: 604, validation: 151, holdout: 84 |
 
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  | `synthetic-relation` | train: 976 |
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  | `sources` | train: 5445 |
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  ## Schemas
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+ - `extraction` / `sources`: `{"input", "output": {"entities":
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  {"named_data", "descriptive_data", "vague_data"}, "entity_descriptions"}}`.
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+ - `extraction` rows carry a `meta` field tagging provenance: `FCV`
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+ (forced-displacement / FCV corpus), `PRWP` (Policy Research Working Papers --
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+ manually annotated + reviewed/validated), or `synthetic` (seed-based synthetic
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+ training data, flat-NER). `train` = FCV + PRWP + synthetic; `validation` and
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+ `test` are FCV-only.
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  - `synthetic-relation`: relation-format synthetic training data (`{"input",
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  "output": {"entities": {"named_data", "organization"}, "relations":
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  [{"<type>": {"head", "tail"}}]}, "_meta"}`) from
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  `relation_training_synthetic` and `relation_llm_generated`, with a `source`
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  column.
 
 
 
 
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  - `relation`: `{"input", "output": {"entities": {"named_data",
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  "organization"}, "relations": [{"<type>": {"head", "tail"}}]}, "_meta"}`
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  with types `has_organization`, `used_by`, `has_acronym`, `has_timeframe`,
extraction/train.jsonl CHANGED
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