Triple
T31515578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kajansi |
E804064
|
entity |
| Predicate | roadDistanceToEntebbe_km |
P172261
|
FINISHED |
| Object | approximately 25 |
—
|
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 25 | Statement: [Kajansi, roadDistanceToEntebbe_km, approximately 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToEntebbe_km Context triple: [Kajansi, roadDistanceToEntebbe_km, approximately 25]
-
A.
distanceFromKampala
Indicates the measured distance between a given location and the city of Kampala.
-
B.
distanceFromJuba_km
Indicates the physical distance, measured in kilometers, between a given location and Juba.
-
C.
distanceToJuba_km
Indicates the physical distance, measured in kilometers, between a given location and Juba.
-
D.
distanceToArusha
Indicates the measured spatial distance between a given entity and the location Arusha.
-
E.
distanceFromNairobi
Indicates the spatial distance between a given entity’s location and the city of Nairobi.
- 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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a9603b208190b3533ea2b441514c |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a915ead881909463ae46419c343e |
completed | May 3, 2026, 1:47 a.m. |
Created at: April 30, 2026, 9:52 p.m.