Triple
T21809810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Advanced Génifique Sensitive Dual Concentrate |
E538440
|
entity |
| Predicate | skinConcern |
P112877
|
FINISHED |
| Object | redness-prone skin |
—
|
LITERAL 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: redness-prone skin | Statement: [Advanced Génifique Sensitive Dual Concentrate, skinConcern, redness-prone skin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skinConcern Context triple: [Advanced Génifique Sensitive Dual Concentrate, skinConcern, redness-prone skin]
-
A.
skinCharacteristic
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
B.
focusesOnSkinConcern
chosen
Indicates that something (such as a product, treatment, or content) is specifically directed toward addressing or improving a particular skin concern.
-
C.
pigmentation
Indicates the presence, type, or degree of coloration in or on an entity.
-
D.
hasFacialSkinColor
Indicates that one entity has a specific facial skin color characterized or attributed by another entity.
-
E.
bodyTreatment
Indicates a treatment or therapeutic procedure that is applied to a person's body.
- F. None of above.
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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc4809c8190853e2777a1f573d4 |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:53 p.m.