Triple
T25459394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nairobi–Johannesburg |
E638000
|
entity |
| Predicate | linksLargestCity |
P94566
|
FINISHED |
| Object | Johannesburg |
—
|
NE NERFINISHED |
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: Johannesburg | Statement: [Nairobi–Johannesburg, linksLargestCity, Johannesburg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linksLargestCity Context triple: [Nairobi–Johannesburg, linksLargestCity, Johannesburg]
-
A.
connectsLargestCitiesOf
chosen
Indicates a relationship where something (typically a route, network, or infrastructure) links together the largest cities within a specified region or set.
-
B.
linkedCity
Indicates that two entities are associated with each other through a specific city, such as being located in, connected via, or related by that city.
-
C.
linkedCapitalCity
Indicates that there is an established association or connection between a given entity and a specific capital city.
-
D.
linksMetropolitanArea
Indicates a relationship where one entity connects or associates a subject with a specific metropolitan area.
-
E.
largestCity
Indicates that one city is the most populous or significant urban center within a specified region or 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f72a452c8190b53c90a8a725dd69 |
completed | May 2, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 2:11 p.m.