Triple
T4465334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuvaluan dollar |
E98363
|
entity |
| Predicate | subunitValue |
P507
|
FINISHED |
| Object | 100 cents = 1 Tuvaluan dollar |
—
|
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 cents = 1 Tuvaluan dollar | Statement: [Tuvaluan dollar, subunitValue, 100 cents = 1 Tuvaluan dollar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subunitValue Context triple: [Tuvaluan dollar, subunitValue, 100 cents = 1 Tuvaluan dollar]
-
A.
subunitType
Indicates that one entity is a specific kind or classification of subunit within the structure or composition of another entity.
-
B.
subunitRatio
chosen
Indicates the proportional relationship between the quantities or sizes of different subunits within a larger whole.
-
C.
subunitOf
Indicates that one entity functions as a component or smaller part within the structure or organization of another, larger entity.
-
D.
subunitSymbol
Indicates that one entity is the symbolic or abbreviated representation (symbol) of a subunit of another entity.
-
E.
hasSubunitName
Indicates that an entity includes or is associated with a named subunit or component as part of its structure or organization.
- 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_69b3454a7c608190944f5455c8031d73 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35697937c8190b91f72d9e4f945f6 |
completed | March 13, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69b34f65f6448190abfadb2ae5658798 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:34 p.m.