Triple
T12896026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shire of Ngaanyatjarraku |
E308494
|
entity |
| Predicate | hasSparsePopulation |
P26438
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Shire of Ngaanyatjarraku, hasSparsePopulation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSparsePopulation Context triple: [Shire of Ngaanyatjarraku, hasSparsePopulation, true]
-
A.
isDenselyPopulated
Indicates that a place has a high concentration of inhabitants relative to its area.
-
B.
hasLowPopulationDensity
chosen
Indicates that the number of individuals or entities per unit area in a given region is relatively small compared to typical or expected levels.
-
C.
hasPopulationDensity
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
-
D.
hasVerySmallResidentPopulation
Indicates that the subject location has a resident population that is extremely small in size.
-
E.
hasPopulationConcentrationIn
Indicates that a population is densely or significantly clustered within a specified geographic area or region.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9717d859481908957510babac2d69 |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:40 p.m.