Triple
T320720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Korean won |
E6407
|
entity |
| Predicate | denominationCode |
P12441
|
FINISHED |
| Object | KRW banknotes and coins |
—
|
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: KRW banknotes and coins | Statement: [South Korean won, denominationCode, KRW banknotes and coins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: denominationCode Context triple: [South Korean won, denominationCode, KRW banknotes and coins]
-
A.
denominationType
Indicates the specific category or kind of denomination associated with an entity, such as its type within a broader classification of denominations.
-
B.
denomination
Indicates the specific religious or organizational branch, sect, or subgroup with which an entity is affiliated.
-
C.
denominationSystem
Indicates a relationship where one entity defines, uses, or belongs to a particular system of denominations (such as units, values, or classifications) established by another entity.
-
D.
banknoteDenomination
Indicates the specific face value assigned to a banknote in a given currency.
-
E.
coinDenomination
Indicates the specific monetary value assigned to a coin within a currency system.
- 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.