Triple
T19175494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 Camp Fire |
E469426
|
entity |
| Predicate | firefighterFatalities |
P134735
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [2018 Camp Fire, firefighterFatalities, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firefighterFatalities Context triple: [2018 Camp Fire, firefighterFatalities, 0]
-
A.
causedFatalities
Indicates that the referenced event or action directly resulted in one or more deaths.
-
B.
constructionAccidentFatalities
Indicates that a construction-related accident resulted in one or more fatalities.
-
C.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
D.
fireRescue
Indicates a relationship where one entity performs or is responsible for rescuing people or property from fires or fire-related emergencies involving another entity.
-
E.
numberOfFirefightersInvolved
Indicates the total count of firefighters who participated in or were involved in a specific event, incident, or operation.
- 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_69d8dd09d5a081909ae43c286651ae5a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f166d3888190adaf6dc8531a8ed1 |
completed | April 20, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69e4b9bb158481909478ca2e06f3ba39 |
completed | April 19, 2026, 11:17 a.m. |
| PDg | Predicate description generation | batch_69e4bfe9ef7081908a74a57d1fc731ea |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:06 p.m.