Triple
T29236819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Registrar General’s Office (Zimbabwe) |
E741215
|
entity |
| Predicate | hasLocalOfficesIn |
P68855
|
FINISHED |
| Object | provinces of Zimbabwe |
—
|
LITERAL 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: provinces of Zimbabwe | Statement: [Registrar General’s Office (Zimbabwe), hasLocalOfficesIn, provinces of Zimbabwe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalOfficesIn Context triple: [Registrar General’s Office (Zimbabwe), hasLocalOfficesIn, provinces of Zimbabwe]
-
A.
hasGlobalOffices
Indicates that an entity maintains offices or physical business locations in multiple countries or regions around the world.
-
B.
mayHaveBranchOfficesIn
Indicates that an entity is permitted or allowed to establish branch offices in a specified location.
-
C.
hasNumberOfRegionalOffices
Indicates the quantity of regional offices that an entity possesses or operates.
-
D.
hasCorporateOffice
Indicates that an entity maintains a formal corporate office at a specified location or within another organizational entity.
-
E.
hasBranchOffice
chosen
Indicates that one organization maintains a branch office or subsidiary location in another place or entity.
- 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_69f0911dd6fc819097d1abb287016489 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
Created at: April 28, 2026, 12:29 p.m.