Triple
T24645861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zongo Falls |
E610107
|
entity |
| Predicate | approxTravelTimeFromKinshasa |
P156895
|
FINISHED |
| Object | about 3 hours by road |
—
|
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 3 hours by road | Statement: [Zongo Falls, approxTravelTimeFromKinshasa, about 3 hours by road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approxTravelTimeFromKinshasa Context triple: [Zongo Falls, approxTravelTimeFromKinshasa, about 3 hours by road]
-
A.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
-
B.
distanceFromBujumbura
Indicates the measured spatial distance between a given location and the city of Bujumbura.
-
C.
distanceToBujumbura_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Bujumbura.
-
D.
distanceFromKigali
Indicates the measured spatial distance between a given location and the city of Kigali.
-
E.
timeToReachNearKhartoum
Indicates the amount of time required for an entity to arrive at or near the location of Khartoum.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
| PDg | Predicate description generation | batch_69f41010f06c81908ee7f773220df14f |
completed | May 1, 2026, 2:29 a.m. |
Created at: April 18, 2026, 2:33 a.m.