Triple
T715428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hendrik Verwoerd |
E14302
|
entity |
| Predicate | officeStartAsMinisterOfNativeAffairs |
P18458
|
FINISHED |
| Object | 1950 |
—
|
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: 1950 | Statement: [Hendrik Verwoerd, officeStartAsMinisterOfNativeAffairs, 1950]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeStartAsMinisterOfNativeAffairs Context triple: [Hendrik Verwoerd, officeStartAsMinisterOfNativeAffairs, 1950]
-
A.
hasMinister
Indicates that one entity serves as the minister (political, religious, or administrative official) responsible for or associated with another entity.
-
B.
typeOfMinistry
Indicates the specific category or kind of ministry that an entity belongs to or represents.
-
C.
hasMediaMinistry
Indicates that an entity operates, oversees, or is associated with a ministry or department responsible for media-related affairs.
-
D.
numberOfMinistries
Indicates the total count of ministries associated with or belonging to a given entity.
-
E.
civilianLeaderDepartment
Indicates that a person serves as the civilian head or chief official of a specified government department or ministry.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a574b4d881908b6d0be386081efd |
completed | March 1, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f38898819089d79bad4f4ff2d2 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.