Triple
T320643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indonesian rupiah |
E6406
|
entity |
| Predicate | frequentlyUsedBanknotes |
P12439
|
FINISHED |
| Object | 1000 rupiah |
—
|
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: 1000 rupiah | Statement: [Indonesian rupiah, frequentlyUsedBanknotes, 1000 rupiah]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentlyUsedBanknotes Context triple: [Indonesian rupiah, frequentlyUsedBanknotes, 1000 rupiah]
-
A.
typeOfBanknotes
Indicates a relationship where one entity specifies the kind or category of banknotes associated with another entity.
-
B.
banknoteDenomination
Indicates the specific face value assigned to a banknote in a given currency.
-
C.
currentBanknoteSeries
Indicates that the subject is part of, or associated with, the banknote series that is currently in official circulation.
-
D.
lastSeriesBanknotesFeatured
Indicates that the referenced banknotes were the most recent series to prominently feature a particular subject or design.
-
E.
languageOnBanknotes
Indicates the language that is printed or used on a country's banknotes.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea8047c08190872c875e00f6e7dd |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea7d03a88190aab72e61d8673488 |
completed | Feb. 28, 2026, 1:15 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.