Triple
T29303766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kibra Sub-county |
E743033
|
entity |
| Predicate | hasInformalSettlement |
P16159
|
FINISHED |
| Object | Kibera |
—
|
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: Kibera | Statement: [Kibra Sub-county, hasInformalSettlement, Kibera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInformalSettlement Context triple: [Kibra Sub-county, hasInformalSettlement, Kibera]
-
A.
hasCityStatusSettlement
Indicates that a settlement possesses official recognition or designation as a city.
-
B.
hasHumanSettlement
chosen
Indicates that a location or area contains or is the site of a human settlement, such as a town, village, or city.
-
C.
hasUrbanVillages
Indicates that an entity contains or includes one or more designated urban villages within its area or jurisdiction.
-
D.
hasInformalMarketNearby
Indicates that an entity is located close to an informal or unregulated market area.
-
E.
hasUrbanLocalities
Indicates that an entity possesses or includes one or more urban localities within its jurisdiction or scope.
- 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_69f09123ed9881909f351f7541933f5e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fe831c97c88190b27ecf100e25c2a0 |
completed | May 9, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69fe7f1b92648190b14e56bcaee5d0ca |
completed | May 9, 2026, 12:26 a.m. |
Created at: April 28, 2026, 1:11 p.m.