Triple
T10254928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Zealand film industry |
E240436
|
entity |
| Predicate | hasLocation |
P40
|
FINISHED |
| Object | Queenstown |
E139271
|
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: Queenstown | Statement: [New Zealand film industry, hasLocation, Queenstown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Queenstown Context triple: [New Zealand film industry, hasLocation, Queenstown]
-
A.
Queenstown
Queenstown is a small historic mining town on Tasmania’s rugged west coast, known for its dramatic landscapes and proximity to wilderness areas.
-
B.
Queenstown
chosen
Queenstown is a popular resort town in New Zealand renowned for its dramatic alpine scenery and adventure tourism activities.
-
C.
Queenstown
Queenstown is an electoral ward in the London Borough of Wandsworth, covering part of the Battersea area in southwest London.
-
D.
Twizel
Twizel is a small town in New Zealand's Mackenzie District, known as a gateway to outdoor activities such as hiking, fishing, and stargazing in the surrounding alpine and lake landscapes.
-
E.
Hāwera
Hāwera is a town in New Zealand known for its dairy industry and as a service and commercial hub in the South Taranaki District.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d24c69ac81908b4da53d13407ac8 |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f7cec62c819083e493e0fc7c65b5 |
completed | April 9, 2026, 12:50 a.m. |
Created at: April 6, 2026, 11:30 a.m.