Triple
T30626797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umkhosi woMhlanga |
E779602
|
entity |
| Predicate | hasMainVenueRegion |
P19090
|
FINISHED |
| Object | northern KwaZulu-Natal |
—
|
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: northern KwaZulu-Natal | Statement: [Umkhosi woMhlanga, hasMainVenueRegion, northern KwaZulu-Natal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainVenueRegion Context triple: [Umkhosi woMhlanga, hasMainVenueRegion, northern KwaZulu-Natal]
-
A.
homeVenueRegion
chosen
Indicates the geographic region in which an entity’s primary or home venue is located.
-
B.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
C.
typicalVenueRegion2
Indicates that a venue is commonly or characteristically located within a particular secondary geographic region.
-
D.
hasVenueIn
Indicates that an event, activity, or occurrence takes place at a specific venue located within a particular geographic area or location.
-
E.
hasVenueScope
Indicates that something is applicable, valid, or restricted specifically within the context or boundaries of a particular venue.
- 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_69f224a431548190a44ad9d088dbf91f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69ffc083a54c8190ac80d05ee8d20a6b |
completed | May 9, 2026, 11:17 p.m. |
| PD | Predicate disambiguation | batch_69ffbfeb05b88190b4d50ce8124004d9 |
completed | May 9, 2026, 11:14 p.m. |
Created at: April 29, 2026, 8:28 p.m.