Triple
T32714160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Court of Appeal of Kenya |
E836474
|
entity |
| Predicate | hasRegistryIn |
P200594
|
FINISHED |
| Object | Nairobi |
E6371
|
NE 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: Nairobi | Statement: [Court of Appeal of Kenya, hasRegistryIn, Nairobi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegistryIn Context triple: [Court of Appeal of Kenya, hasRegistryIn, Nairobi]
-
A.
hasPrincipalRegistryIn
chosen
Indicates that an entity’s primary or main official registration is located in a specified registry or jurisdiction.
-
B.
hasRegister
Indicates that one entity possesses, contains, or is associated with a specific register (such as a record, log, or hardware register).
-
C.
hasRegistrar
Indicates that an entity is formally recorded or overseen by a specific registrar organization or authority.
-
D.
hasRegistryView
Indicates that an entity has permission or capability to access and view a particular registry or registry-related information.
-
E.
hasRegisterSystem
Indicates that an entity uses or is associated with a particular register system (e.g., a system for recording, tracking, or registering items, events, or participants).
- F. None of above.
Provenance (4 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_69f3493446148190819541f3ffe79975 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0309a4e4d481908a6070b40d507aae |
completed | May 12, 2026, 11:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a349eccaf988190b6c923d9dd3d47f0 |
completed | June 19, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_6a03091ac1008190bf50357364d4e9e4 |
completed | May 12, 2026, 11:03 a.m. |
Created at: May 1, 2026, 1:11 a.m.