Triple
T6677617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malibu, California |
E151892
|
entity |
| Predicate | hasWildfireRisk |
P36822
|
FINISHED |
| Object | high |
—
|
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 | Statement: [Malibu, California, hasWildfireRisk, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWildfireRisk Context triple: [Malibu, California, hasWildfireRisk, high]
-
A.
wildfireRisk
chosen
Indicates the likelihood or potential severity of wildfires occurring in a given area or under specific conditions.
-
B.
nearbyWildfire
Indicates that a wildfire is occurring close enough to a given location or entity to be considered in its immediate vicinity.
-
C.
hasNaturalHazardRisk
Indicates that an entity is exposed or subject to potential damage or impact from one or more natural hazards (e.g., earthquakes, floods, storms).
-
D.
hasFireRegime
Indicates that an area or ecosystem is characterized by a particular pattern, frequency, and intensity of fires over time.
-
E.
hasWildernessArea
Indicates that one entity possesses, contains, or is associated with a designated wilderness area.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:03 p.m.