Triple
T20394916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basin Complex Fire |
E500175
|
entity |
| Predicate | typeOfIncident |
P76024
|
FINISHED |
| Object | wildland fire |
—
|
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: wildland fire | Statement: [Basin Complex Fire, typeOfIncident, wildland fire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfIncident Context triple: [Basin Complex Fire, typeOfIncident, wildland fire]
-
A.
notableIncidentType
chosen
Indicates the specific category or kind of significant event or incident associated with an entity.
-
B.
incidentWith
Indicates that one entity is involved in, affected by, or associated with a particular incident or event together with another entity.
-
C.
incidentName
Indicates the specific name or label assigned to an incident within a system or context.
-
D.
stateOfIncident
Indicates the specific condition or status that an incident is currently in within its lifecycle.
-
E.
situationType
Indicates the general kind or category of situation, event, or circumstance that a given instance represents.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e679122058819083e3615a5ea0a82e |
completed | April 20, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69e5765d7cb48190adec18d6d1e3d263 |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:28 a.m.