Triple
T6874376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyalu B5 |
E158635
|
entity |
| Predicate | dermatologicallyTested |
P73863
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hyalu B5, dermatologicallyTested, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dermatologicallyTested Context triple: [Hyalu B5, dermatologicallyTested, true]
-
A.
coFormulatedWith
Indicates that one entity is formulated together with another as part of the same combined product or composition.
-
B.
testedFor
Indicates that an entity has been examined or analyzed to determine the presence, absence, or level of another specified entity or condition.
-
C.
safetyLabel
Indicates that an entity has been assigned a safety-related classification or warning status.
-
D.
skinCharacteristic
Indicates a relationship where an entity is associated with a particular quality, feature, or condition of its skin.
-
E.
establishedTest
Indicates that an entity has created, set up, or formally instituted a test or testing process.
- F. None of above. chosen
Provenance (4 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_69c68832af1481908ce356e133ebaebe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8c8d3888190b1c1f74aa66d6071 |
completed | March 27, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b363dc8190a7225b540ab2bc40 |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c48ba48190b8d3aa7b8d22816b |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:22 p.m.