Triple
T24566459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bual |
E607802
|
entity |
| Predicate | notableFlavorDescriptors |
P149764
|
FINISHED |
| Object | dried fruit |
—
|
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: dried fruit | Statement: [Bual, notableFlavorDescriptors, dried fruit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFlavorDescriptors Context triple: [Bual, notableFlavorDescriptors, dried fruit]
-
A.
notableFlavorNotes
chosen
Indicates that something is characterized by specific, distinguishable flavor notes that are especially prominent or noteworthy.
-
B.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
C.
coffeeFlavorNotes
Indicates the characteristic taste and aroma qualities associated with a particular coffee, such as specific flavor notes perceived when it is consumed.
-
D.
leafTaste
Indicates that one entity has a particular taste or flavor associated with its leaves.
-
E.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
- 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_69e2c4cc35a48190990b7571bc086df8 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a92082a881908896dcdda85559b9 |
completed | April 30, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:28 a.m.