Triple
T7335335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mbombela |
E169111
|
entity |
| Predicate | borderProximityRole |
P67824
|
FINISHED |
| Object | facilitates cross-border trade with Mozambique |
—
|
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: facilitates cross-border trade with Mozambique | Statement: [Mbombela, borderProximityRole, facilitates cross-border trade with Mozambique]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderProximityRole Context triple: [Mbombela, borderProximityRole, facilitates cross-border trade with Mozambique]
-
A.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
-
B.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
C.
borderRegionPresence
Indicates the presence or occurrence of something within or along a border region between areas or territories.
-
D.
borderRegionRole
chosen
Indicates a role or function that an entity has specifically in relation to a border region or border area.
-
E.
borderPoint
Indicates a point that lies on the boundary between two regions or entities.
- 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_69c68a568a6481908f11e20db7bc8446 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.