Triple
T583062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Australia |
E15097
|
entity |
| Predicate | hasPopulationCenterDensity |
P15795
|
FINISHED |
| Object | high along the coast |
—
|
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: high along the coast | Statement: [Eastern Australia, hasPopulationCenterDensity, high along the coast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopulationCenterDensity Context triple: [Eastern Australia, hasPopulationCenterDensity, high along the coast]
-
A.
hasPopulationDensity
Indicates the number of individuals (e.g., people, organisms) per unit area associated with a given entity or region.
-
B.
populationDensity
Indicates the number of individuals or entities occupying a unit area within a given region.
-
C.
hasPopulationCenter
Indicates that an area, region, or administrative unit contains or is served by a primary settlement or population hub.
-
D.
hasPopulationCenterType
Indicates the classification of a population center by its type, such as city, town, village, or other settlement category.
-
E.
hasPopulationApproximate
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b85becc8190b4d98c00e5fa7c04 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494c9315c8190a773e8e00737d8a0 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985a2d08819090947895d9439e06 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:33 p.m.