Triple
T1554242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danish krone |
E33163
|
entity |
| Predicate | frequentlyUsedCoin |
P30283
|
FINISHED |
| Object | 1 krone |
—
|
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: 1 krone | Statement: [Danish krone, frequentlyUsedCoin, 1 krone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentlyUsedCoin Context triple: [Danish krone, frequentlyUsedCoin, 1 krone]
-
A.
rarelyUsedCoins
Indicates that the coins in question are infrequently or almost never used in transactions or everyday circulation.
-
B.
coinedIn
Indicates that something (typically a term, phrase, or name) was first created or introduced at a particular time or in a particular place.
-
C.
isMostTradedCurrency
Indicates that a currency is the one with the highest trading volume or frequency in a given market or context.
-
D.
coinagePower
Indicates the authority or capacity of an entity to create, issue, or regulate currency or coinage.
-
E.
scriptUsedOnCoins
Indicates that a particular writing system or script is used on the inscriptions appearing on coins.
- 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_69a885ee6db8819099502bc5ce8af881 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9407d9d1481909597af97b16512cc |
completed | March 5, 2026, 8:36 a.m. |
| PD | Predicate disambiguation | batch_69a907b688d081908171f89010c53973 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a9407aa20881909e747f247ccec642 |
completed | March 5, 2026, 8:36 a.m. |
Created at: March 4, 2026, 7:27 p.m.