Triple
T27983715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eau de Cologne |
E706690
|
entity |
| Predicate | typicalConcentration |
P39616
|
FINISHED |
| Object | 2–5% aromatic compounds |
—
|
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: 2–5% aromatic compounds | Statement: [Eau de Cologne, typicalConcentration, 2–5% aromatic compounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalConcentration Context triple: [Eau de Cologne, typicalConcentration, 2–5% aromatic compounds]
-
A.
commonConcentration
Indicates that multiple entities share the same concentration level of a specified substance or component.
-
B.
concentration
chosen
Indicates the degree to which a substance or entity is present within a given medium, mixture, or space.
-
C.
concentrationVariant
Indicates that one entity represents a version or form of another that differs specifically in concentration level.
-
D.
concentrationComponent
Indicates that one entity is a constituent or ingredient whose amount contributes to the overall concentration of another entity (such as a mixture, solution, or sample).
-
E.
concentrationClass
Indicates the classification of an entity based on the level or range of its concentration.
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_6a004c41f13c8190bc47daf6a5ca3949 |
completed | May 10, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_6a004bce3e3081909b35ae5b3bf2b35e |
completed | May 10, 2026, 9:11 a.m. |
Created at: April 27, 2026, 7:46 p.m.