Triple
T28413784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Rudd |
E719741
|
entity |
| Predicate | servedAsPrimeMinisterNumber |
P193881
|
FINISHED |
| Object | 26 |
—
|
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: 26 | Statement: [Kevin Rudd, servedAsPrimeMinisterNumber, 26]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedAsPrimeMinisterNumber Context triple: [Kevin Rudd, servedAsPrimeMinisterNumber, 26]
-
A.
numberOfTermsAsPrimeMinister
Indicates how many separate terms an individual has served in the role of prime minister.
-
B.
succeededInOfficeAsPrimeMinisterBy
Indicates that one individual’s term as Prime Minister ended and was directly followed by another individual’s term in that office.
-
C.
servedUnderPrimeMinister
Indicates that one person held a governmental or official position subordinate to, and during the tenure of, a particular prime minister.
-
D.
numberOfPrimeMinisters
Indicates the count of individuals who have held the position of prime minister for a given entity or context.
-
E.
servedAsFirstMinisterWith
Indicates that a person held the position of First Minister in association with a specified government, administration, or jurisdiction.
- F. None of above. chosen
Provenance (4 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_69eff6f0f37c8190b37bc6fab08a9449 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
| PDg | Predicate description generation | batch_69fd592cc56081908ce456114d407616 |
completed | May 8, 2026, 3:31 a.m. |
Created at: April 28, 2026, 1:29 a.m.