Triple
T17050811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Speyside |
E413688
|
entity |
| Predicate | hasCharacteristicFlavor |
P107732
|
FINISHED |
| Object | apple 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: apple notes | Statement: [Speyside, hasCharacteristicFlavor, apple notes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacteristicFlavor Context triple: [Speyside, hasCharacteristicFlavor, apple notes]
-
A.
hasCharacteristic
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
B.
hasFlavorType
chosen
Indicates that an entity possesses or is characterized by a particular type or category of flavor.
-
C.
hasSecondaryFlavor
Indicates that an entity possesses an additional, subordinate flavor characteristic beyond its primary flavor.
-
D.
hasCharacteristicArtifact
Indicates that an entity is associated with a specific artifact that characterizes, exemplifies, or is typical of it.
-
E.
hasCharm
Indicates that an entity possesses or exhibits charm, attractiveness, or an appealing quality.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa26e84819098b41ae15618e813 |
completed | April 18, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.