Triple
T9060431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Fire |
E217106
|
entity |
| Predicate | fireSuppressionForces |
P63388
|
FINISHED |
| Object | thousands of firefighters |
—
|
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: thousands of firefighters | Statement: [Thomas Fire, fireSuppressionForces, thousands of firefighters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fireSuppressionForces Context triple: [Thomas Fire, fireSuppressionForces, thousands of firefighters]
-
A.
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.
-
B.
fireServiceBy
chosen
Indicates that a fire protection or firefighting service is provided, operated, or carried out by a specified agent or organization.
-
C.
fireCoverage
Indicates the extent to which an area or object is protected or served by fire prevention, detection, or suppression resources.
-
D.
firefightingMethods
Indicates the techniques or strategies used to control, contain, or extinguish fires.
-
E.
fireType
Indicates that one entity has a specific classification or category related to fire (e.g., type, kind, or nature of fire).
- 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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7eca6d8c8190b1a11a60d6649f78 |
completed | April 1, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee6d83c819095d8ed0779aa8511 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:10 p.m.