Triple
T2784809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unilever |
E61784
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object |
Tresemmé
Tresemmé is a popular hair care brand known for its salon-inspired shampoos, conditioners, and styling products widely available in retail stores.
|
E297555
|
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: Tresemmé | Statement: [Unilever, hasBrand, Tresemmé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tresemmé Context triple: [Unilever, hasBrand, Tresemmé]
-
A.
Redken
Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
-
B.
Biolage
Biolage is a professional haircare brand known for salon-quality products that emphasize botanical ingredients and sustainable practices.
-
C.
Schwarzkopf
Schwarzkopf is a German surname most prominently associated with U.S. Army General Norman Schwarzkopf Jr., who led coalition forces in the Gulf War.
-
D.
Pureology
Pureology is a professional haircare brand best known for its sulfate-free, color-protecting products used in salons and at home.
-
E.
Revlon
Revlon is a major American cosmetics, skincare, fragrance, and personal care company known for its mass-market beauty products and global brand presence.
- 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: Tresemmé Triple: [Unilever, hasBrand, Tresemmé]
Generated description
Tresemmé is a popular hair care brand known for its salon-inspired shampoos, conditioners, and styling products widely available in retail stores.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tresemmé Target entity description: Tresemmé is a popular hair care brand known for its salon-inspired shampoos, conditioners, and styling products widely available in retail stores.
-
A.
Redken
Redken is a professional haircare and hair color brand known for its salon-quality products and innovative, science-driven formulas.
-
B.
Biolage
Biolage is a professional haircare brand known for salon-quality products that emphasize botanical ingredients and sustainable practices.
-
C.
Schwarzkopf
Schwarzkopf is a German surname most prominently associated with U.S. Army General Norman Schwarzkopf Jr., who led coalition forces in the Gulf War.
-
D.
Pureology
Pureology is a professional haircare brand best known for its sulfate-free, color-protecting products used in salons and at home.
-
E.
Revlon
Revlon is a major American cosmetics, skincare, fragrance, and personal care company known for its mass-market beauty products and global brand presence.
- 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddaf223c8190959bb0b336e5b7c0 |
completed | March 7, 2026, 8:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc0629e8c81909b55d9838e681ba2 |
completed | March 10, 2026, 6:55 a.m. |
| NEDg | Description generation | batch_69afc15513f48190a22f83571be2e0bd |
completed | March 10, 2026, 6:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afc1c9440c8190abf9dc063109af45 |
completed | March 10, 2026, 7:01 a.m. |
Created at: March 6, 2026, 9:57 p.m.