Triple
T1405144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Polish złoty |
E31673
|
entity |
| Predicate | belongsToMonetaryRegion |
P18115
|
FINISHED |
| Object | non-euro EU currencies |
—
|
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: non-euro EU currencies | Statement: [Polish złoty, belongsToMonetaryRegion, non-euro EU currencies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToMonetaryRegion Context triple: [Polish złoty, belongsToMonetaryRegion, non-euro EU currencies]
-
A.
currencyArea
chosen
Indicates that one entity is the geographic or economic region in which the other entity’s currency is officially used or valid.
-
B.
definedMonetarySystem
Indicates that an authority or entity has established and specified the rules, structure, and characteristics of a particular monetary system.
-
C.
beneficiaryRegion
Indicates the region that receives the benefit, advantage, or positive impact resulting from an action, resource, or arrangement.
-
D.
associatedCurrencyCode
Indicates the currency code that is linked to or used in connection with the given entity or transaction.
-
E.
hasMonetaryComponent
Indicates that something includes, involves, or is associated with a monetary or financial element.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3bc55a08190a4dfe13a5378aff3 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf030a388190bc82d30b9233e873 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.