Triple
T33348147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horowhenua-Kapiti |
E853855
|
entity |
| Predicate | partOfCatchmentAreaFor |
P4498
|
FINISHED |
| Object | Hurricanes |
—
|
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: Hurricanes | Statement: [Horowhenua-Kapiti, partOfCatchmentAreaFor, Hurricanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfCatchmentAreaFor Context triple: [Horowhenua-Kapiti, partOfCatchmentAreaFor, Hurricanes]
-
A.
hasCatchmentAreaLocation
Indicates that a catchment area is geographically located in or associated with a specific place or region.
-
B.
hasCatchmentArea
chosen
Indicates that a geographic or administrative unit serves as the area from which an entity (such as a facility or service) draws its users, resources, or influence.
-
C.
attendsSchoolIn
Indicates that a person is enrolled as a student at, and regularly goes to, a school located in a particular place.
-
D.
schoolCatchmentIncludes
Indicates that a school’s designated catchment area geographically includes a given location or region.
-
E.
containsEducationalInstitution
Indicates that one entity geographically or administratively includes or encompasses an educational institution within its boundaries or structure.
- 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_69f3496a1a588190bad9cbe9221144e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ffef812da48190b875a7376b24f92d |
completed | May 10, 2026, 2:37 a.m. |
| PD | Predicate disambiguation | batch_69ffedecd580819097851b1473fdd6ed |
completed | May 10, 2026, 2:31 a.m. |
Created at: May 1, 2026, 1:34 a.m.