Triple
T12890034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuban centavo |
E308334
|
entity |
| Predicate | subdivisionRatio |
P507
|
FINISHED |
| Object | 100 centavos = 1 Cuban peso |
—
|
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 centavos = 1 Cuban peso | Statement: [Cuban centavo, subdivisionRatio, 100 centavos = 1 Cuban peso]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subdivisionRatio Context triple: [Cuban centavo, subdivisionRatio, 100 centavos = 1 Cuban peso]
-
A.
parallelSubdivision
Indicates that one structure or process is divided into multiple parts that proceed or are handled simultaneously alongside each other.
-
B.
subdividedBy
Indicates that something is divided into smaller parts or sections by another entity or criterion.
-
C.
subdivisionRank
Indicates the hierarchical level or type of administrative or territorial subdivision that an entity occupies within a larger organizational or geographic structure.
-
D.
divisionSize
Indicates the size or magnitude of a division or subdivided part in relation to a whole.
-
E.
subunitRatio
chosen
Indicates the proportional relationship between the quantities or sizes of different subunits within a larger whole.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714581988190afc720ffd7797860 |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:39 p.m.