Triple
T21809725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iris gourmand accord |
E538438
|
entity |
| Predicate | balancesContrastBetween |
P123206
|
FINISHED |
| Object | powdery floral 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: powdery floral notes | Statement: [iris gourmand accord, balancesContrastBetween, powdery floral notes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: balancesContrastBetween Context triple: [iris gourmand accord, balancesContrastBetween, powdery floral notes]
-
A.
exploresContrastBetween
Indicates a relationship in which one entity examines, highlights, or analyzes the differences or oppositions between two or more entities, ideas, or situations.
-
B.
achievesContrast
Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
-
C.
contrastUse
Indicates that one entity is used in opposition or distinction to another to highlight differences between them.
-
D.
oftenContrastedWith
Indicates that one entity is frequently compared to another in a way that highlights their differences or opposing characteristics.
-
E.
providesContrastWith
chosen
Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc4809c8190853e2777a1f573d4 |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:53 p.m.