Triple
T17769153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlusconi I Cabinet |
E443586
|
entity |
| Predicate | cabinetNumberInRepublicHistory |
P17175
|
FINISHED |
| Object | 51 |
—
|
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: 51 | Statement: [Berlusconi I Cabinet, cabinetNumberInRepublicHistory, 51]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cabinetNumberInRepublicHistory Context triple: [Berlusconi I Cabinet, cabinetNumberInRepublicHistory, 51]
-
A.
cabinetNumberInHistory
chosen
Indicates the specific cabinet number assigned to an entity within a historical record or context.
-
B.
cabinetOf
Indicates that one entity serves as the cabinet or governing body associated with another entity, typically a state, government, or leader.
-
C.
hasCabinetNumberingSystem
Indicates that there is a specific scheme or method used to assign and organize identification numbers to cabinets.
-
D.
servedInCabinetOf
Indicates that one person held a position as a member of the governmental cabinet led by another person.
-
E.
officeHoldersNumbered
Indicates that a specific office or position has its holders identified and distinguished by assigned numbers (e.g., first holder, second holder, etc.).
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e485fe70648190b4107e1eabacc694 |
completed | April 19, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:11 a.m.