Triple
T9060448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Fire |
E217106
|
entity |
| Predicate | smokeImpact |
P86151
|
FINISHED |
| Object | smoke reached parts of Central and Northern 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: smoke reached parts of Central and Northern California | Statement: [Thomas Fire, smokeImpact, smoke reached parts of Central and Northern California]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: smokeImpact Context triple: [Thomas Fire, smokeImpact, smoke reached parts of Central and Northern California]
-
A.
smokeUse
Indicates that an entity uses or consumes tobacco or other substances by smoking.
-
B.
smokeSystem
Indicates that an entity is equipped with or associated with a smoke-generating system (e.g., for signaling, testing, or special effects).
-
C.
canBeSmoked
Indicates that something is suitable or able to be consumed by smoking.
-
D.
smokeColor
Indicates the color attribute associated with a given instance of smoke.
-
E.
smokingMaterial
Indicates that one entity is a material or substance used for smoking by another entity.
- 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_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. |
| PDg | Predicate description generation | batch_69cc5f4f1cb48190a025d1b3d8d7a790 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:10 p.m.