Triple
T473612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Office of Economic Stabilization |
E9011
|
entity |
| Predicate | reasonForExistence |
P5256
|
FINISHED |
| Object | economic dislocations caused by World War II |
—
|
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: economic dislocations caused by World War II | Statement: [Office of Economic Stabilization, reasonForExistence, economic dislocations caused by World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForExistence Context triple: [Office of Economic Stabilization, reasonForExistence, economic dislocations caused by World War II]
-
A.
reasonForCreation
chosen
Indicates that one entity was created for the purpose, cause, or motivation specified by another entity.
-
B.
reasonForName
Indicates the explanation or cause behind why an entity has a particular name.
-
C.
originalReason
Indicates the initial cause, motivation, or justification behind an action, decision, or state of affairs.
-
D.
reasonForChange
Indicates that one entity serves as the cause, justification, or motivation for a modification or change in another entity or state.
-
E.
selectionReason
Indicates the reason or justification for choosing or selecting one entity over alternatives.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0208c788190a96cdabcf593fda7 |
completed | Feb. 28, 2026, 1:39 p.m. |
| PD | Predicate disambiguation | batch_69a2edeed31881908cf43beed410572d |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.