Triple
T34915199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mata-Mata (Namibia) |
E1006981
|
entity |
| Predicate | locatedWithinOrAdjacentTo |
P50548
|
FINISHED |
| Object | Kgalagadi Transfrontier Park |
E63981
|
NE 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: Kgalagadi Transfrontier Park | Statement: [Mata-Mata (Namibia), locatedWithinOrAdjacentTo, Kgalagadi Transfrontier Park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedWithinOrAdjacentTo Context triple: [Mata-Mata (Namibia), locatedWithinOrAdjacentTo, Kgalagadi Transfrontier Park]
-
A.
locatedInOrAdjacentTo
chosen
Indicates that one entity is either situated within the boundaries of another entity or directly next to it, sharing a common border or edge.
-
B.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
C.
locatedBetween
Indicates that one entity is positioned spatially between two other reference entities.
-
D.
collocatedWith
Indicates that two entities are located in the same place or spatial context at the same time.
-
E.
locatedAlong
Indicates that one entity is situated adjacent to, or running beside, the length or course of another linear feature (such as a road, river, or railway).
- F. None of above.
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_69f76dc2b6b0819095a61debbd405269 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37bd05043881909a4e80ceb7ad575c |
completed | June 21, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.