Triple
T36725637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jinja Airport |
E907186
|
entity |
| Predicate | distanceFromKampalaByRoad |
P46022
|
FINISHED |
| Object | about 95 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 95 kilometres | Statement: [Jinja Airport, distanceFromKampalaByRoad, about 95 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKampalaByRoad Context triple: [Jinja Airport, distanceFromKampalaByRoad, about 95 kilometres]
-
A.
distanceFromKampala
chosen
Indicates the measured distance between a given location and the city of Kampala.
-
B.
roadDistanceToEntebbe_km
Indicates the distance in kilometers between an entity and Entebbe when traveling by road.
-
C.
distanceFromKigali
Indicates the measured spatial distance between a given location and the city of Kigali.
-
D.
distanceToBujumbura_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Bujumbura.
-
E.
distanceFromNairobi
Indicates the spatial distance between a given entity’s location and the city of Nairobi.
- 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_69f76e746e4c8190a0d05cc6d57a643e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:12 p.m.