Triple
T32785959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Court of Kenya |
E838498
|
entity |
| Predicate | hasPrincipalSeat |
P63954
|
FINISHED |
| Object | Nairobi |
—
|
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: Nairobi | Statement: [High Court of Kenya, hasPrincipalSeat, Nairobi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrincipalSeat Context triple: [High Court of Kenya, hasPrincipalSeat, Nairobi]
-
A.
hasPrimarySeat
chosen
Indicates that one entity is designated as the main or principal seat, location, or position associated with another entity.
-
B.
hasExecutiveSeat
Indicates that an entity holds a position or seat with executive authority or decision-making power within an organization or governing body.
-
C.
hasJudicialSeat
Indicates that an entity holds an official position or seat within a judicial body or court.
-
D.
hasSeatAt
Indicates that an entity occupies or holds a place, position, or membership within a specific group, body, or location.
-
E.
hasMunicipalLeaderSeat
Indicates that a specific location serves as the official seat or office location of a municipal leader (e.g., mayor) for a municipality.
- 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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a011e5a419081908d06a07b395ebd97 |
completed | May 11, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_6a011de119048190b27d361cffabc228 |
completed | May 11, 2026, 12:08 a.m. |
Created at: May 1, 2026, 1:14 a.m.