Triple
T9260538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Sudanese pound |
E222564
|
entity |
| Predicate | replacedInTerritory |
P37094
|
FINISHED |
| Object | Sudanese pound in South Sudan |
—
|
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: Sudanese pound in South Sudan | Statement: [South Sudanese pound, replacedInTerritory, Sudanese pound in South Sudan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: replacedInTerritory Context triple: [South Sudanese pound, replacedInTerritory, Sudanese pound in South Sudan]
-
A.
replacedInCountry
chosen
Indicates that one entity has been substituted or superseded by another within the context or jurisdiction of a specific country.
-
B.
renamedTerritory
Indicates that an existing territory has been given a new official name, linking the former designation to its updated one.
-
C.
placedBy
Indicates that one entity was positioned, set, or put in a location or context by another entity.
-
D.
territoryCorrespondedTo
Indicates that one territory matched, aligned with, or was equivalent to another territory in scope, boundaries, or designation.
-
E.
territoryIncluded
Indicates that one territory is geographically or administratively contained within another territory.
- 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_69ca841e4cd481908e738c74e958eaea |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd07160e408190be4bd7b757260a0e |
completed | April 1, 2026, 11:52 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4e79e48190b3200247f4624867 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:32 p.m.