Triple
T11045945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Zealand national parks |
E261135
|
entity |
| Predicate | largestParkArea |
P97471
|
FINISHED |
| Object | over 1200000 hectares |
—
|
LITERAL 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: over 1200000 hectares | Statement: [New Zealand national parks, largestParkArea, over 1200000 hectares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestParkArea Context triple: [New Zealand national parks, largestParkArea, over 1200000 hectares]
-
A.
isLargestParkOf
Indicates that a park is the largest park within a specified area, region, or administrative entity.
-
B.
isLargestUrbanParkIn
Indicates that one entity is the largest urban park within the boundaries or context of another specified entity (such as a city or region).
-
C.
largestNationalPark
Indicates that the subject is the largest national park within the specified country or region.
-
D.
oneOfLargestNationalParksIn
Indicates that the subject is among the largest national parks located within the specified place or region.
-
E.
largestNearbyPark
Indicates that one entity is the park which is both near another entity and is the largest among all such nearby parks.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7982f7e688190b3f0c249cd9b1a3e |
completed | April 9, 2026, 12:14 p.m. |
| PD | Predicate disambiguation | batch_69d74407cb088190ba37c8da3d342b64 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750c99f9881908ee2b01b6ce4b3a1 |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:26 p.m.