Triple
T16861777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Executive Order 9380 |
E409930
|
entity |
| Predicate | warEffortRole |
P108011
|
FINISHED |
| Object | administration of foreign economic policy |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: administration of foreign economic policy | Statement: [Executive Order 9380, warEffortRole, administration of foreign economic policy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: warEffortRole Context triple: [Executive Order 9380, warEffortRole, administration of foreign economic policy]
-
A.
worldWarIIRole
Indicates the specific role, position, or function an entity had in relation to World War II.
-
B.
strategicRoleDuringWar
Indicates that an entity served a particular strategic function or importance during a specific war or armed conflict.
-
C.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
-
D.
roleInWorldWarI
Indicates the specific function, position, or involvement an entity had during World War I.
-
E.
roleInWarOrConflict
chosen
Indicates the specific function, position, or involvement an entity has within a particular war or conflict.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b5036e6c8190a3b9e525a34da2e1 |
completed | April 18, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.