Triple
T142669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Pitt the Younger |
E2885
|
entity |
| Predicate | ageAtFirstBecomingPrimeMinister |
P6808
|
FINISHED |
| Object | 24 |
—
|
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: 24 | Statement: [William Pitt the Younger, ageAtFirstBecomingPrimeMinister, 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageAtFirstBecomingPrimeMinister Context triple: [William Pitt the Younger, ageAtFirstBecomingPrimeMinister, 24]
-
A.
primeMinisterTermStart
Indicates the date on which an individual officially begins serving as prime minister.
-
B.
firstPrimeMinister
Indicates that one entity is the first person to hold the office of prime minister of the other entity.
-
C.
predecessorAsPrimeMinister
Indicates that one person previously held the office of Prime Minister immediately before another person.
-
D.
firstInOfficeTo
Indicates that one entity was the earliest or first to hold a particular office or position in relation to another entity or context.
-
E.
producedMostPrimeMinistersOf
Indicates that the subject entity has produced a greater number of prime ministers than any other comparable entity within a specified context.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565559ac81909e0c4e095a7dfa27 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2580b00988190868ee24c0289cf70 |
completed | Feb. 28, 2026, 2:50 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.