Triple
T29747073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Court of Uganda |
E752782
|
entity |
| Predicate | hasPrincipalRegistryIn |
P200594
|
FINISHED |
| Object | Kampala |
—
|
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: Kampala | Statement: [High Court of Uganda, hasPrincipalRegistryIn, Kampala]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrincipalRegistryIn Context triple: [High Court of Uganda, hasPrincipalRegistryIn, Kampala]
-
A.
hasRegistrar
Indicates that an entity is formally recorded or overseen by a specific registrar organization or authority.
-
B.
hasRegistrationAuthority
Indicates that an entity is formally overseen, recorded, or certified by a specific authority responsible for its registration.
-
C.
hasPrincipleSet
Indicates that an entity is associated with or governed by a specific set of principles.
-
D.
hasRegister
Indicates that one entity possesses, contains, or is associated with a specific register (such as a record, log, or hardware register).
-
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. chosen
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_69f0d62b064081908c1ae61cd68fb139 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff9a25407c81909faa86e72a7a9d17 |
completed | May 9, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69ff99c613688190a03b2f93d5ccad2b |
completed | May 9, 2026, 8:32 p.m. |
| PDg | Predicate description generation | batch_69ff9a24996c8190ba2c5345d317cbdb |
completed | May 9, 2026, 8:33 p.m. |
Created at: April 28, 2026, 7:51 p.m.