Triple
T5179988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ventana Wilderness |
E116894
|
entity |
| Predicate | fireHistory |
P19591
|
FINISHED |
| Object | subject to large wildfires |
—
|
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: subject to large wildfires | Statement: [Ventana Wilderness, fireHistory, subject to large wildfires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fireHistory Context triple: [Ventana Wilderness, fireHistory, subject to large wildfires]
-
A.
hasFireHistory
chosen
Indicates that an entity has experienced one or more fire events in the past.
-
B.
hasFireRegime
Indicates that an area or ecosystem is characterized by a particular pattern, frequency, and intensity of fires over time.
-
C.
fires
Indicates that an agent initiates the discharge or ignition of something, such as a weapon, engine, or explosive device, causing it to operate or go off.
-
D.
fireType
Indicates that one entity has a specific classification or category related to fire (e.g., type, kind, or nature of fire).
-
E.
notableFire
Indicates that a significant or historically important fire event is associated with the subject.
- 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_69bd446140f08190becb93c61158f27f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd799a322c8190b8a590cfe70761f5 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b529948190b86671ebe43f4734 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:45 p.m.