Triple
T25641667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skoal |
E642851
|
entity |
| Predicate | healthWarning |
P61651
|
FINISHED |
| Object | is not a safe alternative to cigarettes |
—
|
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: is not a safe alternative to cigarettes | Statement: [Skoal, healthWarning, is not a safe alternative to cigarettes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthWarning Context triple: [Skoal, healthWarning, is not a safe alternative to cigarettes]
-
A.
warningSigns
Indicates that one entity presents or serves as cautionary indications or alerts about potential danger, problems, or undesirable outcomes related to another entity.
-
B.
hasHealthWarningOnPackaging
Indicates that an item’s packaging displays a health-related warning message or symbol.
-
C.
dangerWarning
chosen
Indicates that one entity issues or represents a warning about potential danger associated with another entity or situation.
-
D.
healthTheme
Indicates that the subject is associated with, focuses on, or is characterized by a particular health-related topic or theme.
-
E.
observationSafety
Indicates that an observation or monitoring activity is conducted in a manner that ensures the safety of the subjects, observers, and environment involved.
- 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_69e77e7ce28081908b08d65ee6e5c8be |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fa660fa0819087e2711cee51d7a1 |
completed | May 2, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 5:44 p.m.