Triple
T24389861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heber-Overgaard, Arizona |
E614855
|
entity |
| Predicate | wildfireHistory |
P19591
|
FINISHED |
| Object | affected by Rodeo–Chediski Fire in 2002 |
—
|
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: affected by Rodeo–Chediski Fire in 2002 | Statement: [Heber-Overgaard, Arizona, wildfireHistory, affected by Rodeo–Chediski Fire in 2002]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wildfireHistory Context triple: [Heber-Overgaard, Arizona, wildfireHistory, affected by Rodeo–Chediski Fire in 2002]
-
A.
wildfireRisk
Indicates the likelihood or potential severity of wildfires occurring in a given area or under specific conditions.
-
B.
hasFireManagement
Indicates that an entity implements, practices, or is subject to strategies, policies, or actions for controlling, mitigating, or using fire.
-
C.
hasFireRegime
Indicates that an area or ecosystem is characterized by a particular pattern, frequency, and intensity of fires over time.
-
D.
nearbyWildfire
Indicates that a wildfire is occurring close enough to a given location or entity to be considered in its immediate vicinity.
-
E.
hasFireHistory
chosen
Indicates that an entity has experienced one or more fire events in the past.
- 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_69e2d7e509b88190a53155d4f3de45ce |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29457a0d08190ad19b55625d7a437 |
completed | April 29, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:04 a.m.