Triple
T1554237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danish krone |
E33163
|
entity |
| Predicate | frequentlyUsedBanknote |
P12439
|
FINISHED |
| Object | 50 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: 50 krone | Statement: [Danish krone, frequentlyUsedBanknote, 50 krone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentlyUsedBanknote Context triple: [Danish krone, frequentlyUsedBanknote, 50 krone]
-
A.
frequentlyUsedBanknotes
chosen
Indicates that the referenced banknotes are commonly or regularly used in transactions within a given context or system.
-
B.
typeOfBanknotes
Indicates a relationship where one entity specifies the kind or category of banknotes associated with another entity.
-
C.
banknoteDenomination
Indicates the specific face value assigned to a banknote in a given currency.
-
D.
hasBanknotes
Indicates that an entity possesses or contains one or more banknotes.
-
E.
issuesBanknotes
Indicates that an entity (typically a central bank or monetary authority) produces and puts banknotes into official circulation as legal tender.
- 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_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. |
Created at: March 4, 2026, 7:27 p.m.