Triple
T36310822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gucha District |
E894061
|
entity |
| Predicate | hadUrbanCouncil |
P13025
|
FINISHED |
| Object | Ogembo Town Council |
—
|
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: Ogembo Town Council | Statement: [Gucha District, hadUrbanCouncil, Ogembo Town Council]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadUrbanCouncil Context triple: [Gucha District, hadUrbanCouncil, Ogembo Town Council]
-
A.
hasCityCouncil
chosen
Indicates that an entity is governed or administered by a specific city council.
-
B.
wasUrbanDistrict
Indicates that an entity previously held the status of an urban district within an administrative or governmental hierarchy.
-
C.
wasUrbanStatus
Indicates that an entity previously held an urban classification or status during a specified time period.
-
D.
hasUrbanSectionsIn
Indicates that an entity includes or contains sections that are classified as urban within a specified area or region.
-
E.
hadCity
Indicates that an entity was formerly associated with or located in a particular city.
- 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_69f76e4c1b248190b10667d0213537fe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.