Triple
T8566114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deputy Prime Ministers of Italy |
E202805
|
entity |
| Predicate | numberOfSimultaneousOfficeHolders |
P3416
|
FINISHED |
| Object | one or more |
—
|
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: one or more | Statement: [Deputy Prime Ministers of Italy, numberOfSimultaneousOfficeHolders, one or more]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSimultaneousOfficeHolders Context triple: [Deputy Prime Ministers of Italy, numberOfSimultaneousOfficeHolders, one or more]
-
A.
officeHolderCountIncludes
Indicates that a specified count or total explicitly includes the number of individuals holding a particular office or position.
-
B.
firstOfficeHoldersCount
Indicates the number of individuals who initially held a particular office or position.
-
C.
officeHoldersNumber
chosen
Indicates the number of individuals who hold a particular office or position.
-
D.
officeHoldersNumberLimit
Indicates a constraint specifying the maximum number of individuals who may simultaneously hold a particular office or position.
-
E.
hasListOfOfficeHolders
Indicates that an entity is associated with a collection or record enumerating the individuals who have held a particular office or position.
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe9d467c08190b2014d71ebbf8bbc |
completed | March 31, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69cbd11856048190a1ce4b83a38f6965 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:20 p.m.