Triple
T5083422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balwearie High School |
E114577
|
entity |
| Predicate | hasCatchmentAreaSize |
P61191
|
FINISHED |
| Object | large |
—
|
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: large | Statement: [Balwearie High School, hasCatchmentAreaSize, large]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCatchmentAreaSize Context triple: [Balwearie High School, hasCatchmentAreaSize, large]
-
A.
hasCatchmentArea
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.
-
B.
catchmentArea
Indicates the geographic area from which something (such as a facility, service, or natural feature) draws or collects people, resources, or water.
-
C.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
-
D.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
E.
hasCollectionArea
Indicates that an entity is associated with a specific geographic or spatial area from which items, specimens, or data are collected.
- 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_69bd443dbf908190a9401e9c2dc7bd7d |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7517af308190bab5507a9344bf68 |
completed | March 20, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69bd7159adc881909effd4382c395c66 |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd73b2c2808190b777e2c2a8a45d3f |
completed | March 20, 2026, 4:20 p.m. |
Created at: March 20, 2026, 1:39 p.m.