Triple
T27983725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eau de Cologne |
E706690
|
entity |
| Predicate | secondaryNotes |
P188774
|
FINISHED |
| Object | herbal notes |
—
|
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: herbal notes | Statement: [Eau de Cologne, secondaryNotes, herbal notes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryNotes Context triple: [Eau de Cologne, secondaryNotes, herbal notes]
-
A.
secondarySee
Indicates that one entity is referenced as an additional or alternative point of consultation or viewing in relation to another entity.
-
B.
secondaryTo
Indicates that one condition, event, or factor occurs as a consequence of, or is caused by, another primary condition, event, or factor.
-
C.
secondaryIssue
Indicates that one issue is related to another as a subordinate, less primary, or follow-up concern in the overall context.
-
D.
sideNote
Indicates that an additional, secondary, or tangential piece of information is attached to something as a side remark or annotation.
-
E.
secondaryInterest
Indicates that an entity has a secondary, less primary but still relevant interest or focus in relation to another entity or topic.
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbad1b3ba08190ad69e21461333f2e |
completed | May 6, 2026, 9:05 p.m. |
Created at: April 27, 2026, 7:46 p.m.