Triple
T827911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giorgia Meloni |
E17896
|
entity |
| Predicate | electedToOffice |
P1239
|
FINISHED |
| Object | Chamber of Deputies of Italy in 2006 |
—
|
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: Chamber of Deputies of Italy in 2006 | Statement: [Giorgia Meloni, electedToOffice, Chamber of Deputies of Italy in 2006]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electedToOffice Context triple: [Giorgia Meloni, electedToOffice, Chamber of Deputies of Italy in 2006]
-
A.
electedOffice
chosen
Indicates that an entity holds or has held a particular office or position as a result of an election.
-
B.
nominatedForOffice
Indicates that an entity has been formally put forward as a candidate to hold a particular office or position.
-
C.
succeededInOffice
Indicates that one officeholder directly followed another in holding the same official position.
-
D.
electedWith
Indicates that one entity attained an elected position or office together with, or as part of the same electoral outcome as, another entity.
-
E.
appointedOrElected
Indicates that an entity attained a position, role, or office through either an appointment process or an electoral process.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab99b1e48190afad1f073348b29a |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa79a6488190a634388e071ed9b7 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.