Triple
T2403682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenvue |
E50225
|
entity |
| Predicate | ownsBrand |
P1500
|
FINISHED |
| Object |
Nicorette
Nicorette is a leading nicotine replacement therapy brand offering products like gum, lozenges, and patches to help people quit smoking.
|
E262877
|
NE FINISHED |
How this triple was built (4 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: Nicorette | Statement: [Kenvue, ownsBrand, Nicorette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nicorette Context triple: [Kenvue, ownsBrand, Nicorette]
-
A.
Listerine
Listerine is a widely used antiseptic mouthwash brand known for its strong flavor and plaque- and germ-fighting oral care products.
-
B.
Wrigley’s Spearmint
Wrigley’s Spearmint is a classic spearmint-flavored chewing gum brand known for its long-lasting flavor and iconic green packaging.
-
C.
Tareyton
Tareyton is a former American cigarette brand best known for its long-running “Us Tareyton smokers would rather fight than switch” advertising campaign featuring smokers with black eyes.
-
D.
Doublemint
Doublemint is a popular Wrigley chewing gum brand known for its long-lasting mint flavor and iconic twin-themed advertising.
-
E.
Blistex
Blistex is an American company best known for producing lip care and other medicated skin care products.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nicorette Triple: [Kenvue, ownsBrand, Nicorette]
Generated description
Nicorette is a leading nicotine replacement therapy brand offering products like gum, lozenges, and patches to help people quit smoking.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nicorette Target entity description: Nicorette is a leading nicotine replacement therapy brand offering products like gum, lozenges, and patches to help people quit smoking.
-
A.
Listerine
Listerine is a widely used antiseptic mouthwash brand known for its strong flavor and plaque- and germ-fighting oral care products.
-
B.
Wrigley’s Spearmint
Wrigley’s Spearmint is a classic spearmint-flavored chewing gum brand known for its long-lasting flavor and iconic green packaging.
-
C.
Tareyton
Tareyton is a former American cigarette brand best known for its long-running “Us Tareyton smokers would rather fight than switch” advertising campaign featuring smokers with black eyes.
-
D.
Doublemint
Doublemint is a popular Wrigley chewing gum brand known for its long-lasting mint flavor and iconic twin-themed advertising.
-
E.
Blistex
Blistex is an American company best known for producing lip care and other medicated skin care products.
- F. None of above. chosen
Provenance (5 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc8f8aa2881909192920ee394f0b3 |
completed | March 7, 2026, 6:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3e740c88190872aa1a7834d73b0 |
completed | March 9, 2026, 11:49 a.m. |
| NEDg | Description generation | batch_69aeb4b942b08190addc2885fbda0e41 |
completed | March 9, 2026, 11:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69aeb557247c8190920ce3a5db388800 |
completed | March 9, 2026, 11:56 a.m. |
Created at: March 4, 2026, 7:58 p.m.