Triple
T1904647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberian dollar |
E37772
|
entity |
| Predicate | coexistsInPracticeWith |
P12845
|
FINISHED |
| Object | cash U.S. dollars |
—
|
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: cash U.S. dollars | Statement: [Liberian dollar, coexistsInPracticeWith, cash U.S. dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coexistsInPracticeWith Context triple: [Liberian dollar, coexistsInPracticeWith, cash U.S. dollars]
-
A.
coexistedWith
chosen
Indicates that two entities existed at the same time and in the same context or environment, without implying any specific type of interaction between them.
-
B.
coincidesWith
Indicates that two entities occupy the same position, time, or state such that they exactly overlap or occur together.
-
C.
administeredAlongside
Indicates that one treatment, drug, or intervention is given or applied at the same time as another.
-
D.
operatedAlongside
Indicates that two or more entities functioned or were active together in a coordinated or concurrent manner within the same context or system.
-
E.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
- 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_69a8861be7148190a680937ec451a304 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafe9f8b0819086d8f6288511c66d |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.