Triple
T29353475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mityana District |
E744373
|
entity |
| Predicate | distanceFromKampala_km |
P46022
|
FINISHED |
| Object | approximately 70 |
—
|
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 70 | Statement: [Mityana District, distanceFromKampala_km, approximately 70]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKampala_km Context triple: [Mityana District, distanceFromKampala_km, approximately 70]
-
A.
distanceFromKampala
chosen
Indicates the measured distance between a given location and the city of Kampala.
-
B.
distanceFromNairobi
Indicates the spatial distance between a given entity’s location and the city of Nairobi.
-
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.
roadDistanceToEntebbe_km
Indicates the distance in kilometers between an entity and Entebbe when traveling by road.
- 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_69f0a79a2d748190bc30abd469298b37 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a0079e152648190a9da2add94fc1831 |
completed | May 10, 2026, 12:28 p.m. |
| PD | Predicate disambiguation | batch_6a0078f77f9c8190af357a6016a2bd53 |
completed | May 10, 2026, 12:24 p.m. |
Created at: April 28, 2026, 2:08 p.m.