Triple
T1791656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Zimbabwe |
E39507
|
entity |
| Predicate | distanceFromMasvingo |
P31971
|
FINISHED |
| Object | approximately 30 kilometers southeast |
—
|
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: approximately 30 kilometers southeast | Statement: [Great Zimbabwe, distanceFromMasvingo, approximately 30 kilometers southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMasvingo Context triple: [Great Zimbabwe, distanceFromMasvingo, approximately 30 kilometers southeast]
-
A.
distanceToHarare
Indicates the spatial distance between a given entity and the location of Harare.
-
B.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
-
C.
distanceToHoniaraApprox
Indicates an approximate distance measurement between a given entity’s location and the location of Honiara.
-
D.
distanceFromCapeTown
Indicates the measured distance between a given location and Cape Town.
-
E.
distanceToSouthAfrica
Indicates the measured or calculated spatial distance between a given entity and the country of South Africa.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab61b6ea188190aab9fb839bf1e367 |
completed | March 6, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69aa61d2f7a8819090301f92d3e358c7 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab61b5c8988190bb2b46182a4eb5b4 |
completed | March 6, 2026, 11:22 p.m. |
Created at: March 4, 2026, 7:32 p.m.