Triple
T3655654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capricornia |
E77522
|
entity |
| Predicate | containsRuralAreas |
P14399
|
FINISHED |
| Object | central Queensland rural regions |
—
|
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: central Queensland rural regions | Statement: [Capricornia, containsRuralAreas, central Queensland rural regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsRuralAreas Context triple: [Capricornia, containsRuralAreas, central Queensland rural regions]
-
A.
hasRuralArea
chosen
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
B.
hasRuralCommunes
Indicates that an entity possesses, includes, or is associated with one or more rural communes.
-
C.
isInRuralAreaOf
Indicates that one entity is located within the rural area or countryside region associated with another entity.
-
D.
isPredominantlyRural
Indicates that a place or region is characterized mainly by rural features, such as low population density and extensive non-urban land use.
-
E.
hasSuburbanAreas
Indicates that a place includes or is associated with surrounding residential suburban districts or neighborhoods.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3baf57c8190b72b5d1b910d9db6 |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb84650148190bf79231105e58d7f |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.