Triple
T4775707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Paradise |
E106039
|
entity |
| Predicate | wildfireImpact |
P43620
|
FINISHED |
| Object | widespread destruction of structures |
—
|
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: widespread destruction of structures | Statement: [Town of Paradise, wildfireImpact, widespread destruction of structures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wildfireImpact Context triple: [Town of Paradise, wildfireImpact, widespread destruction of structures]
-
A.
wildfireRisk
Indicates the likelihood or potential severity of wildfires occurring in a given area or under specific conditions.
-
B.
bushfiresImpact
chosen
Indicates how bushfires affect or influence other entities, conditions, or outcomes.
-
C.
nearbyWildfire
Indicates that a wildfire is occurring close enough to a given location or entity to be considered in its immediate vicinity.
-
D.
hasFireRegime
Indicates that an area or ecosystem is characterized by a particular pattern, frequency, and intensity of fires over time.
-
E.
conservationImpact
Indicates the effect that an action, policy, or entity has on the preservation, protection, or restoration of natural ecosystems and biodiversity.
- 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_69bd43f3074c8190937e7b0a457fe9f1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd69237f80819090713ed62653fb75 |
completed | March 20, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69bd622be1388190ab5511b589c878c0 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.