Triple
T1961494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Commissioner for Southern Africa |
E42596
|
entity |
| Predicate | officeHolderAlsoHeld |
P8468
|
FINISHED |
| Object | Governor of the Cape Colony |
—
|
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: Governor of the Cape Colony | Statement: [High Commissioner for Southern Africa, officeHolderAlsoHeld, Governor of the Cape Colony]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderAlsoHeld Context triple: [High Commissioner for Southern Africa, officeHolderAlsoHeld, Governor of the Cape Colony]
-
A.
officePreviouslyHeldBy
Indicates that a particular office or position was formerly occupied by a specified person or entity.
-
B.
alsoHoldsOfficeOf
chosen
Indicates that an entity currently holding one office or position simultaneously holds another office or position as well.
-
C.
officeHolderMayBe
Indicates that a specified person is permitted or eligible to hold a particular office or position.
-
D.
officeHolderAsOf
Indicates that a person holds or held a specific office or position as of a particular date or point in time.
-
E.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
- 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_69a88711151c8190940b2572095059d7 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb68a8e608190bc37a85913b3cd44 |
completed | March 7, 2026, 5:24 a.m. |
| PD | Predicate disambiguation | batch_69abaff5dbd48190a9d36ca60de151db |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.