Triple
T25336980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California’s State Responsibility Area wildlands |
E635302
|
entity |
| Predicate | wildfireRiskDriver |
P158214
|
FINISHED |
| Object | steep topography |
—
|
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: steep topography | Statement: [California’s State Responsibility Area wildlands, wildfireRiskDriver, steep topography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wildfireRiskDriver Context triple: [California’s State Responsibility Area wildlands, wildfireRiskDriver, steep topography]
-
A.
wildfireRiskDriver
chosen
Indicates a factor or condition that contributes to or influences the level of wildfire risk.
-
B.
wildfireRisk
Indicates the likelihood or potential severity of wildfires occurring in a given area or under specific conditions.
-
C.
methodOfKillingWildfire
Indicates the method or technique used to kill or extinguish a wildfire.
-
D.
fireEcologyRole
Indicates the role or function an entity has in ecological processes related to fire, such as how it influences, responds to, or depends on fire within an ecosystem.
-
E.
hasFireRegime
Indicates that an area or ecosystem is characterized by a particular pattern, frequency, and intensity of fires over time.
- 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_69e75a99bd6481909476115b35b9a8e4 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f498b39adc8190b0fc4925ce0769ed |
completed | May 1, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 1:32 p.m.