Triple
T2190447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Listerine |
E49848
|
entity |
| Predicate | brandOwner |
P347
|
FINISHED |
| Object | Kenvue |
E50225
|
NE 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: Kenvue | Statement: [Listerine, brandOwner, Kenvue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kenvue Context triple: [Listerine, brandOwner, Kenvue]
-
A.
Kenvue
chosen
Kenvue is a consumer health company that owns well-known over-the-counter medicine and personal care brands formerly housed within Johnson & Johnson.
-
B.
Johnson & Johnson
Johnson & Johnson is a multinational healthcare conglomerate best known for its pharmaceuticals, medical devices, and consumer health products.
-
C.
Danaher Corporation
Danaher Corporation is a diversified global science and technology conglomerate known for its portfolio of life sciences, diagnostics, and industrial solutions businesses.
-
D.
Lonza
Lonza is a global Swiss-based life sciences company specializing in pharmaceutical, biotech, and nutrition products and services, particularly in contract development and manufacturing.
-
E.
Abbott Laboratories
Abbott Laboratories is a global healthcare company that develops and manufactures medical devices, diagnostics, branded generic medicines, and nutritional products.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf3f5e008190beda3ce5d77209e0 |
completed | March 7, 2026, 6:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5db0352c8190aa9c4c58460df3a4 |
completed | March 9, 2026, 5:42 a.m. |
Created at: March 4, 2026, 7:46 p.m.