Triple
T1466577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stewart Island / Rakiura |
E27035
|
entity |
| Predicate | percentageProtectedAsNationalPark |
P21616
|
FINISHED |
| Object | about 85 percent |
—
|
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: about 85 percent | Statement: [Stewart Island / Rakiura, percentageProtectedAsNationalPark, about 85 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageProtectedAsNationalPark Context triple: [Stewart Island / Rakiura, percentageProtectedAsNationalPark, about 85 percent]
-
A.
percentageOfLandInNationalPark
chosen
Indicates the proportion of a given area’s total land that lies within designated national park boundaries.
-
B.
withinNationalPark
Indicates that one entity is located inside the geographic boundaries of a national park designated by another entity.
-
C.
nationalPark
Indicates that a location is designated and managed as a national park by a governing authority.
-
D.
managesProtectedArea
Indicates that an entity has responsibility for overseeing, administering, and caring for a designated protected area.
-
E.
partOfProtectedAreaCategory
Indicates that one protected area belongs to, or is classified under, a specific protected area category.
- 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_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5bcfa0881909d6137c69825bc7a |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48121e48190946c23c583e5fb64 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.