Triple
T320650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indonesian rupiah |
E6406
|
entity |
| Predicate | frequentlyUsedCoins |
P515
|
FINISHED |
| Object | 100 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: 100 rupiah | Statement: [Indonesian rupiah, frequentlyUsedCoins, 100 rupiah]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentlyUsedCoins Context triple: [Indonesian rupiah, frequentlyUsedCoins, 100 rupiah]
-
A.
coinedIn
Indicates that something (typically a term, phrase, or name) was first created or introduced at a particular time or in a particular place.
-
B.
isMostTradedCurrency
Indicates that a currency is the one with the highest trading volume or frequency in a given market or context.
-
C.
coinDenominationsInclude
chosen
Indicates that a set of coin denominations contains a particular denomination as one of its members.
-
D.
frequentlyTradedAgainst
Indicates that two entities are commonly exchanged or traded with each other in a significant number of transactions over time.
-
E.
coinDenomination
Indicates the specific monetary value assigned to a coin within a currency system.
- 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_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. |
Created at: Feb. 28, 2026, 1:08 p.m.