Triple
T34349255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chitungwiza |
E881519
|
entity |
| Predicate | isDormitoryTownFor |
P178901
|
FINISHED |
| Object | Harare |
—
|
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: Harare | Statement: [Chitungwiza, isDormitoryTownFor, Harare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDormitoryTownFor Context triple: [Chitungwiza, isDormitoryTownFor, Harare]
-
A.
isTown
Indicates that the subject entity is classified as a town.
-
B.
isInteriorTownOf
Indicates that one town is located within the interior region of, and is administratively or geographically associated with, a larger area or jurisdiction.
-
C.
isMunicipalHomeOf
Indicates that a municipality serves as the official home base or hosting location for a particular entity or organization.
-
D.
isResidentialTown
Indicates that a town is primarily used or designated for residential living rather than for commercial, industrial, or other primary purposes.
-
E.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
- 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_69f349bd06008190904c2f86c42749e3 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f717836f0c8190b4a397bbac37dd09 |
completed | May 3, 2026, 9:38 a.m. |
| PD | Predicate disambiguation | batch_69f7127a2ff08190b77d00963c9df621 |
completed | May 3, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69f71782422c81908196d5e4a610cb1a |
completed | May 3, 2026, 9:38 a.m. |
Created at: May 1, 2026, 1:58 a.m.