Triple
T248209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South African rand |
E5083
|
entity |
| Predicate | denominationCoins |
P2872
|
FINISHED |
| Object | 10 cents |
—
|
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: 10 cents | Statement: [South African rand, denominationCoins, 10 cents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: denominationCoins Context triple: [South African rand, denominationCoins, 10 cents]
-
A.
coinDenomination
chosen
Indicates the specific monetary value assigned to a coin within a currency system.
-
B.
denominationType
Indicates the specific category or kind of denomination associated with an entity, such as its type within a broader classification of denominations.
-
C.
coinDenominationsInclude
Indicates that a set of coin denominations contains a particular denomination as one of its members.
-
D.
denomination
Indicates the specific religious or organizational branch, sect, or subgroup with which an entity is affiliated.
-
E.
banknoteDenomination
Indicates the specific face value assigned to a banknote in a given currency.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d154ebc819087a5c9dc4f62ff44 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b64ea3081908de626a0e1445bdb |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.