Triple
T17682538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlusconi III Cabinet |
E440804
|
entity |
| Predicate | numberOfCabinet |
P128559
|
FINISHED |
| Object | 59th government of the Italian Republic |
—
|
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: 59th government of the Italian Republic | Statement: [Berlusconi III Cabinet, numberOfCabinet, 59th government of the Italian Republic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCabinet Context triple: [Berlusconi III Cabinet, numberOfCabinet, 59th government of the Italian Republic]
-
A.
cabinetType
Indicates the specific kind or category of cabinet associated with an entity.
-
B.
hasCabinet
Indicates that one entity possesses, includes, or is equipped with a cabinet associated with it.
-
C.
cabinet
Indicates that one entity serves as a cabinet (a storage or enclosure unit) for another entity.
-
D.
cabinetRequires
Indicates that a particular cabinet depends on or needs another specified item, condition, or component to be present or satisfied.
-
E.
hasCabinetNumberingSystem
Indicates that there is a specific scheme or method used to assign and organize identification numbers to cabinets.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4704514d481908aad4172fa930e6b |
completed | April 19, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69e3cde3673c8190a889e14ba1f07dc1 |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10:02 a.m.