Triple
T27361352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kent Menthol |
E685832
|
entity |
| Predicate | hasNicotine |
P101039
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kent Menthol, hasNicotine, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNicotine Context triple: [Kent Menthol, hasNicotine, yes]
-
A.
containsNicotine
chosen
Indicates that the subject has nicotine as one of its components or ingredients.
-
B.
isNicotineDeliveryProduct
Indicates that a product functions to deliver nicotine to a user, typically through inhalation, ingestion, or absorption.
-
C.
nicotineLevel
Indicates the amount or concentration of nicotine present in or associated with an entity.
-
D.
nicotineForm
Indicates the specific physical or chemical form in which nicotine is present or delivered (e.g., gum, patch, vapor, tobacco).
-
E.
hasNicotineVariants
Indicates that one entity offers or includes different forms, strengths, or types of nicotine associated with another entity.
- 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_69ef14887c288190931b8431fdbf53c4 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f62c23b91c8190a430caf3791f932e |
completed | May 2, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 11:53 a.m.