Triple
T34619841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigerian pound |
E888970
|
entity |
| Predicate | subunitToPound |
P507
|
FINISHED |
| Object | 20 shillings = 1 pound |
—
|
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: 20 shillings = 1 pound | Statement: [Nigerian pound, subunitToPound, 20 shillings = 1 pound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subunitToPound Context triple: [Nigerian pound, subunitToPound, 20 shillings = 1 pound]
-
A.
valueFractionOfPound
Indicates that a given value represents a fractional amount of one pound (as a proportion or part of a full pound).
-
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.
typicalSubunitOf
Indicates that something is a standard or commonly occurring subcomponent or part of a larger whole.
-
E.
subunitType
Indicates that one entity is a specific kind or classification of subunit within the structure or composition of another entity.
- 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_69f349d584e08190b40b9f6281ad50c4 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7234bcaa48190ac970759d34e254a |
completed | May 3, 2026, 10:28 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:03 a.m.