Triple
T35675111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ministry of the Interior (Cisleithania) |
E1030835
|
entity |
| Predicate | hadCabinetLevel |
P1269
|
FINISHED |
| Object | minister |
—
|
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: minister | Statement: [Ministry of the Interior (Cisleithania), hadCabinetLevel, minister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadCabinetLevel Context triple: [Ministry of the Interior (Cisleithania), hadCabinetLevel, minister]
-
A.
cabinetLevel
chosen
Indicates that an official, position, or body holds a status equivalent to or recognized as part of a national cabinet-level rank or authority.
-
B.
hasCabinetRole
Indicates that an entity holds or is assigned a specific role or position within a cabinet (such as a governmental or executive cabinet).
-
C.
cabinetOf
Indicates that one entity serves as the cabinet or governing body associated with another entity, typically a state, government, or leader.
-
D.
servedInCabinetOf
Indicates that one person held a position as a member of the governmental cabinet led by another person.
-
E.
hadSecretary
Indicates that one entity employed or was served by another entity in the role of a secretary.
- 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_69f76e0acfc0819082c8495c2210ce73 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79fe3a7f88190b68858ec9d19904b |
completed | May 3, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69f79e4d885881908a3612e2e75cf84f |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:05 p.m.