Triple
T21809994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rénergie Yeux |
E538445
|
entity |
| Predicate | recommendedUseContext |
P37480
|
FINISHED |
| Object | daily skin-care routine |
—
|
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: daily skin-care routine | Statement: [Rénergie Yeux, recommendedUseContext, daily skin-care routine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recommendedUseContext Context triple: [Rénergie Yeux, recommendedUseContext, daily skin-care routine]
-
A.
recommendsUseOf
Indicates that one entity advises, endorses, or suggests the use of another entity as appropriate or beneficial in a given context.
-
B.
originalUseContext
Indicates the original situation, setting, or context in which something was intended to be used or applied.
-
C.
recommendedMode
Indicates that one entity is suggested or advised as the preferred mode, method, or way of doing or experiencing something in relation to another entity.
-
D.
promotesUseIn
Indicates that one entity actively encourages, supports, or increases the adoption or application of another entity within a particular context or setting.
-
E.
hasTypicalUseContext
chosen
Indicates that something is commonly or characteristically used within a particular situation, setting, or context.
- 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_69f07cc5fd948190a404a050404db975 |
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.