Triple
T35320874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kampala |
E1020034
|
entity |
| Predicate | roadDistanceToGuluInKilometres |
P182732
|
FINISHED |
| Object | about 300 |
—
|
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 300 | Statement: [Kampala, roadDistanceToGuluInKilometres, about 300]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadDistanceToGuluInKilometres Context triple: [Kampala, roadDistanceToGuluInKilometres, about 300]
-
A.
distanceFromKampala
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.
distanceToArusha
Indicates the measured spatial distance between a given entity and the location Arusha.
-
D.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
-
E.
distanceFromJuba_km
Indicates the physical distance, measured in kilometers, between a given location and Juba.
- 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_69f76de9d45c81908a2ed0956b448b65 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79099b9508190934ec3469af1f827 |
completed | May 3, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69f78e2f52e08190a77661223a96c601 |
completed | May 3, 2026, 6:04 p.m. |
| PDg | Predicate description generation | batch_69f78f629d508190b755848162c4e101 |
completed | May 3, 2026, 6:09 p.m. |
Created at: May 3, 2026, 4:03 p.m.