Triple
T37945832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sebastian Kurz |
E946603
|
entity |
| Predicate | wasYoungestChancellorAge |
P189811
|
FINISHED |
| Object | 31 |
—
|
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: 31 | Statement: [Sebastian Kurz, wasYoungestChancellorAge, 31]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasYoungestChancellorAge Context triple: [Sebastian Kurz, wasYoungestChancellorAge, 31]
-
A.
wasYoungestChancellorOf
Indicates that the subject served as the youngest person ever to hold the office of chancellor of the specified entity.
-
B.
wasYoungestHeadOfState
Indicates that the subject held the position of head of state at a time when they were younger than any other person who had ever held that role up to that point.
-
C.
ageAtFirstBecomingPrimeMinister
Indicates the age a person was when they first assumed the office of prime minister.
-
D.
isYoungestToHoldTitle
Indicates that the subject is the youngest individual ever to have held the specified title or position.
-
E.
precededInOfficeAsChancellorBy
Indicates that one individual assumed the role of Chancellor after another specific individual, who held the office immediately before them.
- 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_69f76ef531ac8190ae6d99e5786e76ec |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbca6c066c8190a1599202f341417f |
completed | May 6, 2026, 11:10 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fbc993caa881908c16c3e21efaeef9 |
completed | May 6, 2026, 11:07 p.m. |
Created at: May 3, 2026, 4:20 p.m.