Triple
T4725518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hwange National Park |
E104873
|
entity |
| Predicate | distanceFromVictoriaFalls |
P59053
|
FINISHED |
| Object | about 100 kilometres |
—
|
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: about 100 kilometres | Statement: [Hwange National Park, distanceFromVictoriaFalls, about 100 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromVictoriaFalls Context triple: [Hwange National Park, distanceFromVictoriaFalls, about 100 kilometres]
-
A.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
-
B.
sharesVictoriaFallsWith
Indicates that two entities both have Victoria Falls within their territories or boundaries.
-
C.
distanceToHarare
Indicates the spatial distance between a given entity and the location of Harare.
-
D.
distanceFromMasvingo
Indicates the spatial distance between a given location and Masvingo.
-
E.
distanceToJohannesburg_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Johannesburg.
- F. None of above. chosen
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_69bd43ed84648190ae0b7ee8e8d00482 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6220071881909670c89d072ffb6d |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd67c895dc8190ba648002ff54424b |
completed | March 20, 2026, 3:29 p.m. |
Created at: March 20, 2026, 1:18 p.m.