Triple
T2576097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vuse |
E57777
|
entity |
| Predicate | hasHealthWarning |
P2399
|
FINISHED |
| Object | nicotine is an addictive chemical |
—
|
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: nicotine is an addictive chemical | Statement: [Vuse, hasHealthWarning, nicotine is an addictive chemical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthWarning Context triple: [Vuse, hasHealthWarning, nicotine is an addictive chemical]
-
A.
hasHealthConcern
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
B.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
C.
warnsAbout
chosen
Indicates that one entity alerts or cautions another entity about a potential danger, risk, or problem.
-
D.
hasHazardSignage
Indicates that appropriate warning or hazard signs are present to alert people to potential dangers associated with the entity.
-
E.
hasContraindication
Indicates that one entity (such as a treatment, drug, or procedure) should not be used or performed in the presence of another entity (such as a condition, factor, or co-medication) because it may cause harm or adverse effects.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3a606e481909bcea46de468bb99 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.