Triple
T5601325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aurukun |
E147125
|
entity |
| Predicate | remotenessClassification |
P3560
|
FINISHED |
| Object | very remote community |
—
|
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: very remote community | Statement: [Aurukun, remotenessClassification, very remote community]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: remotenessClassification Context triple: [Aurukun, remotenessClassification, very remote community]
-
A.
remoteness
chosen
Indicates the degree of physical or conceptual distance or isolation between entities.
-
B.
isInRuralAreaOf
Indicates that one entity is located within the rural area or countryside region associated with another entity.
-
C.
isRuralOrUrban
Indicates whether an entity is classified as being in a rural area or an urban area.
-
D.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
E.
featuresRegionalProximity
Indicates that one entity is located near or in close geographic proximity to a particular region or another entity.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020da519c81908626b243e40db263 |
completed | March 22, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69c01b1890ec8190b9e6fa488792e4d4 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:39 p.m.