Triple
T11731173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IQOS |
E278898
|
entity |
| Predicate | doesNotEliminate |
P5512
|
FINISHED |
| Object | health risks from tobacco use |
—
|
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: health risks from tobacco use | Statement: [IQOS, doesNotEliminate, health risks from tobacco use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doesNotEliminate Context triple: [IQOS, doesNotEliminate, health risks from tobacco use]
-
A.
doesNotAbolish
chosen
Indicates that one entity, action, or law does not eliminate, revoke, or put an end to another.
-
B.
doesNot
Indicates that a specified entity lacks, refrains from, or fails to perform a particular action or exhibit a particular property in relation to another entity or context.
-
C.
doesNotCure
Indicates that an action, treatment, or intervention fails to eliminate or resolve a condition, problem, or disease in the affected entity.
-
D.
doesNotDetermine
Indicates that one entity or factor does not uniquely fix, decide, or specify the state, value, or outcome of another.
-
E.
doesNotProtect
Indicates that an entity fails to provide protection or safeguarding to another entity or object.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4d94de08190a7184cf26d8cb94e |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.