Triple
T34484090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngāti Hauā |
E885268
|
entity |
| Predicate | hasUrbanMembersIn |
P179740
|
FINISHED |
| Object | Hamilton |
—
|
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: Hamilton | Statement: [Ngāti Hauā, hasUrbanMembersIn, Hamilton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanMembersIn Context triple: [Ngāti Hauā, hasUrbanMembersIn, Hamilton]
-
A.
hasUrbanSectionsIn
Indicates that an entity includes or contains sections that are classified as urban within a specified area or region.
-
B.
hasUrbanPopulationIn
Indicates that an entity has a specified urban population within a particular geographic area or administrative unit.
-
C.
hasUrbanUnits
Indicates that an entity possesses or includes one or more urban units (such as cities, towns, or urbanized areas) within its scope or structure.
-
D.
hasUrbanFunction
Indicates that an entity serves a specific role or purpose within an urban context, such as providing services, infrastructure, or activities typical of a city environment.
-
E.
hasUrbanDistrictCount
Indicates the number of urban districts associated with a given entity.
- 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_69f349c947fc81909d30b53c194d6ea1 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f727bde8f88190ad746ca515134ca1 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72739c30c81908642eef3feb3afcf |
completed | May 3, 2026, 10:45 a.m. |
| PDg | Predicate description generation | batch_69f727bd39b081908457590c3ba9b745 |
completed | May 3, 2026, 10:47 a.m. |
Created at: May 1, 2026, 2:01 a.m.