Triple
T37545969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Even Better Clinical serum |
E933463
|
entity |
| Predicate | skinTypeSuitability |
P8035
|
FINISHED |
| Object | all skin types |
—
|
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: all skin types | Statement: [Even Better Clinical serum, skinTypeSuitability, all skin types]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skinTypeSuitability Context triple: [Even Better Clinical serum, skinTypeSuitability, all skin types]
-
A.
skinUse
Indicates that one entity uses, applies, or treats the skin of another entity in some manner.
-
B.
skinCharacteristic
chosen
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
C.
focusesOnSkinConcern
Indicates that something (such as a product, treatment, or content) is specifically directed toward addressing or improving a particular skin concern.
-
D.
effectOnSkin
Indicates the impact or influence that something has on the condition, appearance, or health of skin.
-
E.
makeupType
Indicates the specific kind or category of makeup associated with an entity.
- 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_69f76eca55bc8190acf25741793d5dac |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.