Triple
T1379165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Roche-Posay |
E29296
|
entity |
| Predicate | hasProductLine |
P3585
|
FINISHED |
| Object |
Rosaliac
Rosaliac is a La Roche-Posay skincare line formulated to soothe, strengthen, and visibly reduce redness in sensitive, redness-prone skin.
|
E158637
|
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: Rosaliac | Statement: [La Roche-Posay, hasProductLine, Rosaliac]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosaliac Context triple: [La Roche-Posay, hasProductLine, Rosaliac]
-
A.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
-
B.
Gruchy
Gruchy is a small hamlet in the Normandy region of France, best known as the birthplace of the painter Jean-François Millet.
-
C.
Lucilla
Lucilla was a Roman imperial princess and daughter of Emperor Marcus Aurelius who became Empress as the wife of Lucius Verus and was later implicated in a plot against her brother Commodus.
-
D.
Soral
Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
-
E.
Wilella
Wilella is the full given name of American novelist Willa Cather, renowned for her works depicting frontier life on the Great Plains.
- 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: Rosaliac Triple: [La Roche-Posay, hasProductLine, Rosaliac]
Generated description
Rosaliac is a La Roche-Posay skincare line formulated to soothe, strengthen, and visibly reduce redness in sensitive, redness-prone skin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rosaliac Target entity description: Rosaliac is a La Roche-Posay skincare line formulated to soothe, strengthen, and visibly reduce redness in sensitive, redness-prone skin.
-
A.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
-
B.
Gruchy
Gruchy is a small hamlet in the Normandy region of France, best known as the birthplace of the painter Jean-François Millet.
-
C.
Lucilla
Lucilla was a Roman imperial princess and daughter of Emperor Marcus Aurelius who became Empress as the wife of Lucius Verus and was later implicated in a plot against her brother Commodus.
-
D.
Soral
Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
-
E.
Wilella
Wilella is the full given name of American novelist Willa Cather, renowned for her works depicting frontier life on the Great Plains.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c3187f248190a5813274b0ef944d |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acd48a48fc81908b156c273cb5dfc0 |
completed | March 8, 2026, 1:44 a.m. |
| NEDg | Description generation | batch_69acd77d879881908decae7056bfd277 |
completed | March 8, 2026, 1:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acd81c7c1081908b65ca5a57f8706e |
completed | March 8, 2026, 1:59 a.m. |
Created at: March 1, 2026, 7:59 p.m.