Triple
T3808707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rim Fire 2013 (affected area) |
E93074
|
entity |
| Predicate | fireCauseContext |
P51962
|
FINISHED |
| Object | human-caused wildfire |
—
|
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: human-caused wildfire | Statement: [Rim Fire 2013 (affected area), fireCauseContext, human-caused wildfire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fireCauseContext Context triple: [Rim Fire 2013 (affected area), fireCauseContext, human-caused wildfire]
-
A.
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.
-
B.
fallCause
Indicates that one event or condition causes or brings about another event of falling or decline.
-
C.
fireAdaptation
Indicates that an entity possesses traits or mechanisms that enable it to survive, reproduce, or otherwise benefit in environments where fire occurs.
-
D.
notableFire
Indicates that a significant or historically important fire event is associated with the subject.
-
E.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
- F. None of above. chosen
Provenance (4 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_69aed96a60088190ab1df8390fffc935 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7482d708190a3ec74745b102a4c |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef14f9bb4819098e64b527b546d74 |
completed | March 9, 2026, 4:11 p.m. |
Created at: March 9, 2026, 3:16 p.m.