Triple
T1776530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Softsoap liquid hand soap |
E38991
|
entity |
| Predicate | safetyLabel |
P32294
|
FINISHED |
| Object | for external use only |
—
|
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: for external use only | Statement: [Softsoap liquid hand soap, safetyLabel, for external use only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyLabel Context triple: [Softsoap liquid hand soap, safetyLabel, for external use only]
-
A.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
-
B.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
C.
hasSafetyRegulationCompliance
Indicates that an entity adheres to, satisfies, or is in conformity with specified safety regulations or standards.
-
D.
safetyEquipment
Indicates that one entity serves as safety equipment used to protect another entity from harm or danger.
-
E.
safetyRequirement
Indicates that one entity specifies or imposes conditions, standards, or measures necessary to ensure the safety of another entity or activity.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab74dc9d1481908084ef07872a71f8 |
completed | March 7, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69aa61cf3ca881908641fd73ce2f7c9d |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab74db3dbc8190ab256a4e158062b8 |
completed | March 7, 2026, 12:44 a.m. |
Created at: March 4, 2026, 7:31 p.m.