Triple
T9060412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Fire |
E217106
|
entity |
| Predicate | ignitionPoint |
P56348
|
FINISHED |
| Object | near Thomas Aquinas College, Santa Paula, California |
—
|
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: near Thomas Aquinas College, Santa Paula, California | Statement: [Thomas Fire, ignitionPoint, near Thomas Aquinas College, Santa Paula, California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ignitionPoint Context triple: [Thomas Fire, ignitionPoint, near Thomas Aquinas College, Santa Paula, California]
-
A.
ignitionMethod
Indicates the specific way or mechanism by which something is ignited or set on fire.
-
B.
fireType
Indicates that one entity has a specific classification or category related to fire (e.g., type, kind, or nature of fire).
-
C.
burnCapability
Indicates that an entity has the ability or potential to burn, ignite, or cause combustion under certain conditions.
-
D.
fireBeganAt
chosen
Indicates that the event of a fire starting occurred at a specific time or location.
-
E.
isCombustible
Indicates that a substance or material is capable of catching fire and burning under certain conditions.
- 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.