Triple
T10189703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premier of Niue |
E237999
|
entity |
| Predicate | officeNumberOfHolders |
P36886
|
FINISHED |
| Object | multiple since 1974 |
—
|
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: multiple since 1974 | Statement: [Premier of Niue, officeNumberOfHolders, multiple since 1974]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeNumberOfHolders Context triple: [Premier of Niue, officeNumberOfHolders, multiple since 1974]
-
A.
typicalNumberOfHolders
Indicates the usual or expected number of entities that hold or possess a given item, role, or resource.
-
B.
totalNumberOfHolders
chosen
Indicates the total count of distinct entities that hold or possess a given asset, item, or resource.
-
C.
sharesHeldBy
Indicates that a specified number or portion of shares is owned or held by a particular entity.
-
D.
numberOfHoldings
Indicates the quantity of distinct holdings or assets associated with an entity.
-
E.
maximumNumberOfHolders
Indicates the greatest allowable or observed count of entities that can simultaneously hold or possess a given item, role, or resource.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded7d6fdc81908052866495b6574f |
completed | April 2, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:12 p.m.