Triple
T12552251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judith Collins |
E300124
|
entity |
| Predicate | notableOfficeType |
P5164
|
FINISHED |
| Object | senior ministerial roles |
—
|
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: senior ministerial roles | Statement: [Judith Collins, notableOfficeType, senior ministerial roles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableOfficeType Context triple: [Judith Collins, notableOfficeType, senior ministerial roles]
-
A.
hasOfficeType
chosen
Indicates that an entity’s office is classified as a specific type or category of office.
-
B.
notableOfficeStatus
Indicates that an entity holds or has held a particularly significant or distinguished official position or office.
-
C.
notableOrganizationType
Indicates that an organization is recognized as being of a particular notable or significant type or category.
-
D.
notableServiceType
Indicates that the subject is associated with a particular type or category of service that is especially notable or significant.
-
E.
notableBusinessType
Indicates that an entity is notably associated with, characterized by, or best known for a particular type of business.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d95410d0b0819097646edd1b837104 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:58 p.m.