Triple
T38359129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diepsloot |
E1046420
|
entity |
| Predicate | hasMunicipalRegion |
P196371
|
FINISHED |
| Object | Region A of City of Johannesburg |
—
|
NE NERFINISHED |
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: Region A of City of Johannesburg | Statement: [Diepsloot, hasMunicipalRegion, Region A of City of Johannesburg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalRegion Context triple: [Diepsloot, hasMunicipalRegion, Region A of City of Johannesburg]
-
A.
hasMunicipalDistrict
Indicates that an administrative entity includes or is divided into one or more municipal districts as its subordinate units.
-
B.
isMunicipalityInRegion
Indicates that a municipality is located within and administratively belongs to a specific region.
-
C.
hasMunicipalPart
Indicates that an administrative or territorial entity includes a municipality as one of its constituent parts.
-
D.
hasMunicipalArea
chosen
Indicates that an entity (typically an administrative unit or municipality) possesses or is associated with a specific municipal area.
-
E.
hasMunicipalAgglomeration
Indicates that one administrative or geographic entity is part of, or associated with, a larger municipal agglomeration encompassing multiple urban or suburban areas.
- 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_69f76e3a94fc81908edc175e8d259e80 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fedfd913f48190bdcd450980868d9a |
completed | May 9, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fedf58c6e88190821a7156054c9086 |
completed | May 9, 2026, 7:16 a.m. |
Created at: May 3, 2026, 4:31 p.m.