Triple
T2791486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kangaroo Island |
E61937
|
entity |
| Predicate | bushfiresImpact |
P43620
|
FINISHED |
| Object | significant environmental damage |
—
|
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: significant environmental damage | Statement: [Kangaroo Island, bushfiresImpact, significant environmental damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bushfiresImpact Context triple: [Kangaroo Island, bushfiresImpact, significant environmental damage]
-
A.
wildfireRisk
Indicates the likelihood or potential severity of wildfires occurring in a given area or under specific conditions.
-
B.
humanImpact
Indicates the effect or influence that human activities have on another entity, system, or environment.
-
C.
hasFireRegime
Indicates that an area or ecosystem is characterized by a particular pattern, frequency, and intensity of fires over time.
-
D.
climateChangeEffect
Indicates how climate change influences or alters a particular entity, condition, or process.
-
E.
notableFire
Indicates that a significant or historically important fire event is associated with the subject.
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdeea881481908d759c72798a50fb |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd025c948190a97dd961a9592bac |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abdee94c2081908e5075e87e70780a |
completed | March 7, 2026, 8:16 a.m. |
Created at: March 6, 2026, 9:58 p.m.