Triple
T1904623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberian dollar |
E37772
|
entity |
| Predicate | oftenNotUsedFor |
P7974
|
FINISHED |
| Object | large international transactions |
—
|
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: large international transactions | Statement: [Liberian dollar, oftenNotUsedFor, large international transactions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenNotUsedFor Context triple: [Liberian dollar, oftenNotUsedFor, large international transactions]
-
A.
notTypicallyUsedFor
chosen
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
B.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
C.
doesNotUse
Indicates that one entity intentionally refrains from employing, utilizing, or relying on another entity, method, or resource.
-
D.
usedPrimarilyIn
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
-
E.
notObservedIn
Indicates that a particular entity, event, or property has not been detected, recorded, or seen within a specified context, dataset, or environment.
- 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.