Triple
T29354521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakasero Market |
E744399
|
entity |
| Predicate | hasCityCenterProximity |
P36605
|
FINISHED |
| Object | city centre of Kampala |
—
|
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: city centre of Kampala | Statement: [Nakasero Market, hasCityCenterProximity, city centre of Kampala]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityCenterProximity Context triple: [Nakasero Market, hasCityCenterProximity, city centre of Kampala]
-
A.
hasUrbanProximity
Indicates that one entity is located near or within easy access to an urban area associated with another entity.
-
B.
isFartherFromCityCenterThan
Indicates that one location is at a greater distance from the city center than another location.
-
C.
hasCoordinateInCityCentreApprox
Indicates that an entity’s location is approximately within the central area of a city, based on its geographic coordinates.
-
D.
nearbyUrbanCenter
chosen
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
E.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
- 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_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc53f4f881908dcc698687bbb64d |
completed | May 3, 2026, 7:42 a.m. |
Created at: April 28, 2026, 2:09 p.m.