Triple
T31466517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australia (Māori diaspora) |
E802732
|
entity |
| Predicate | hasMajorUrbanCommunitiesIn |
P316
|
FINISHED |
| Object | Sydney |
—
|
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: Sydney | Statement: [Australia (Māori diaspora), hasMajorUrbanCommunitiesIn, Sydney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorUrbanCommunitiesIn Context triple: [Australia (Māori diaspora), hasMajorUrbanCommunitiesIn, Sydney]
-
A.
hasMajorCity
chosen
Indicates that a location possesses at least one city of significant size, importance, or influence within its region or country.
-
B.
hasMostOfUrbanAreasOf
Indicates that one entity contains or encompasses the majority of the urban areas belonging to another entity.
-
C.
hasSemiUrbanCommunities
Indicates that an entity includes or is associated with communities that exhibit both urban and rural characteristics.
-
D.
hasMajorCityOfUse
Indicates that a particular city is the primary or most significant location where something (e.g., a product, language, service) is predominantly used or applied.
-
E.
hasMajorSettlementsType
Indicates that an entity is associated with major settlements of a specified type (e.g., cities, towns, villages).
- 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_69f348c84c1c81908739f100ecf7394e |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a0027e4a59481909417b2531daaf480 |
completed | May 10, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_6a0026a42bc08190ad3322ce625a523a |
completed | May 10, 2026, 6:33 a.m. |
Created at: April 30, 2026, 9:23 p.m.