Triple
T25484285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moloi-Motsepe |
E638656
|
entity |
| Predicate | notableBearerFieldOfActivity |
P39276
|
FINISHED |
| Object | fashion |
—
|
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: fashion | Statement: [Moloi-Motsepe, notableBearerFieldOfActivity, fashion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableBearerFieldOfActivity Context triple: [Moloi-Motsepe, notableBearerFieldOfActivity, fashion]
-
A.
notableActivityIn
Indicates that an entity is particularly recognized for performing a significant activity within a specified place, context, or domain.
-
B.
notableYearOfActivity
Indicates the specific year during which an entity was particularly active, prominent, or notable in its activities or impact.
-
C.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
-
D.
notableField
chosen
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
-
E.
hasNotableBearerOccupation
Indicates that an entity is associated with a notable person who holds a specific occupation.
- 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_69e75dbabeac8190bab30628f8b799d4 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: April 21, 2026, 2:32 p.m.