Triple
T20568591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solberg Cabinet |
E505029
|
entity |
| Predicate | numberOfMenInFirstCabinet |
P140603
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Solberg Cabinet, numberOfMenInFirstCabinet, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMenInFirstCabinet Context triple: [Solberg Cabinet, numberOfMenInFirstCabinet, 11]
-
A.
numberOfCabinetMembers
Indicates the total count of cabinet members associated with a given government, administration, or leader.
-
B.
hasNumberOfMinisters
Indicates the specific count of ministers associated with an entity, such as a government, cabinet, or organization.
-
C.
servedInCabinetOf
Indicates that one person held a position as a member of the governmental cabinet led by another person.
-
D.
numberOfPrimeMinisters
Indicates the count of individuals who have held the position of prime minister for a given entity or context.
-
E.
firstReturnedMembersToParliamentInCentury
Indicates that the subject is the first entity whose members were returned to Parliament during the specified century.
- 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a7a3fdc08190a34dcf4c4e51f078 |
completed | April 20, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69e59ff0116c8190a163ff28ed01430a |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:39 a.m.