Triple
T12452053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunsilk |
E297554
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Head & Shoulders |
E339788
|
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: Head & Shoulders | Statement: [Sunsilk, competitor, Head & Shoulders]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Head & Shoulders Context triple: [Sunsilk, competitor, Head & Shoulders]
-
A.
Head & Shoulders
chosen
Head & Shoulders is a widely known anti-dandruff shampoo and hair care brand owned by Procter & Gamble.
-
B.
Pantene
Pantene is a globally recognized hair care brand known for its shampoos, conditioners, and styling products that emphasize hair health and shine.
-
C.
Sunsilk
Sunsilk is a popular global hair care brand known for its shampoos and conditioners, owned by the multinational company Unilever.
-
D.
Lifebuoy
Lifebuoy is a long-established global soap and hygiene brand known for its antibacterial products and health-focused marketing.
-
E.
Herbal Essences
Herbal Essences is a popular hair care brand known for its fragranced shampoos and conditioners often marketed with botanical and natural imagery.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d9fa5f0819080ca9f6efa212c59 |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f16e87c8190b7e9f61561ae865a |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:56 p.m.