Triple
T2570316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austrians |
E57648
|
entity |
| Predicate | currencyCountry |
P39835
|
FINISHED |
| Object | euro |
—
|
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: euro | Statement: [Austrians, currencyCountry, euro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currencyCountry Context triple: [Austrians, currencyCountry, euro]
-
A.
currencyArea
Indicates that one entity is the geographic or economic region in which the other entity’s currency is officially used or valid.
-
B.
currencyFamily
Indicates that two currencies belong to the same broader monetary family or classification, typically sharing a common origin, standard, or structural framework.
-
C.
currencyType
Indicates the specific kind of monetary unit or currency associated with an entity or transaction.
-
D.
currencyProject
Indicates a relationship where a project is associated with, uses, or is denominated in a particular currency.
-
E.
currencyNumber
Indicates the numerical value or denomination associated with a specific currency.
- F. None of above. chosen
Provenance (4 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd382928c8190b6316f3db48d8e73 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd251b48c8190862c7b39ea1bf8ea |
completed | March 7, 2026, 7:22 a.m. |
Created at: March 6, 2026, 9:48 p.m.