Triple
T6874386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyalu B5 |
E158635
|
entity |
| Predicate | safetyTestedOn |
P60540
|
FINISHED |
| Object | sensitive skin under dermatological control |
—
|
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: sensitive skin under dermatological control | Statement: [Hyalu B5, safetyTestedOn, sensitive skin under dermatological control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyTestedOn Context triple: [Hyalu B5, safetyTestedOn, sensitive skin under dermatological control]
-
A.
testedOn
chosen
Indicates that an entity has been used as the subject or material in a test, experiment, or evaluation performed by another entity.
-
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.
measuresSafetyUsing
Indicates that an entity evaluates or assesses safety by employing a specified method, tool, or standard.
-
D.
establishedTest
Indicates that an entity has created, set up, or formally instituted a test or testing process.
-
E.
hasSafetyCharacteristic
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
- 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_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. |
Created at: March 27, 2026, 2:22 p.m.