Triple
T23589990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matteo Renzi |
E582448
|
entity |
| Predicate | tookOfficeAsPrimeMinisterAtAge |
P6808
|
FINISHED |
| Object | 39 |
—
|
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: 39 | Statement: [Matteo Renzi, tookOfficeAsPrimeMinisterAtAge, 39]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookOfficeAsPrimeMinisterAtAge Context triple: [Matteo Renzi, tookOfficeAsPrimeMinisterAtAge, 39]
-
A.
ageAtFirstBecomingPrimeMinister
chosen
Indicates the age a person was when they first assumed the office of prime minister.
-
B.
endTimeFirstTermAsPrimeMinister
Indicates the date and time when an individual’s first term serving as prime minister comes to an end.
-
C.
primeMinisterAtStart
Indicates that the subject was serving as prime minister at the beginning of a specified period or event.
-
D.
primeMinisterTermStart
Indicates the date on which an individual officially begins serving as prime minister.
-
E.
timeInOfficeBeginsIn
Indicates the point in time or date when an entity’s term, tenure, or period in office starts.
- 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_69e248f9e0a08190814772847003b1ff |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b03484e4819093d5c14c891f7744 |
completed | April 29, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69f118c96a0081908a8ac98ef7e7e60c |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:41 p.m.