Triple
T4822338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manukau Harbour |
E107738
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Onehunga |
E240421
|
NE 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: Onehunga | Statement: [Manukau Harbour, near, Onehunga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Onehunga Context triple: [Manukau Harbour, near, Onehunga]
-
A.
Onehunga
chosen
Onehunga is a suburb of Auckland, New Zealand, known for its diverse multicultural community and strong Pacific Island, particularly Tongan, presence.
-
B.
Matakohe
Matakohe is a small rural settlement in New Zealand best known for its Kauri Museum and historic connections to the kauri gum and timber industries.
-
C.
Opononi
Opononi is a small coastal settlement in New Zealand known for its scenic Hokianga Harbour views and historic seaside charm.
-
D.
Nausori
Nausori is a town in Fiji located near the capital Suva on the island of Viti Levu, known for its airport and role as a regional commercial center.
-
E.
Onerahi
Onerahi is a coastal suburb of Whangārei in Northland, New Zealand, known for its harbour views and proximity to Whangārei Airport.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd43f9efa081908314cb3e94fa1695 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6caa95ec8190bea525dbf3a00477 |
completed | March 20, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be778a642081908761067765ba09c8 |
completed | March 21, 2026, 10:48 a.m. |
Created at: March 20, 2026, 1:24 p.m.