Triple
T10398792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winston White |
E245088
|
entity |
| Predicate | hasBlendCharacteristic |
P56866
|
FINISHED |
| Object | milder blend |
—
|
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: milder blend | Statement: [Winston White, hasBlendCharacteristic, milder blend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBlendCharacteristic Context triple: [Winston White, hasBlendCharacteristic, milder blend]
-
A.
typicalBlendStyle
Indicates the usual or characteristic way in which two or more elements are combined or mixed together.
-
B.
usedInBlends
chosen
Indicates that something serves as an ingredient or component within one or more mixtures, combinations, or blends.
-
C.
hasBrightOrchestrationOrTexture
Indicates that the music exhibits a vivid, clear, or shimmering orchestral sound or instrumental texture.
-
D.
hasAlbedo
Indicates that an entity possesses a specific reflectivity or albedo value, describing how much incoming light it reflects.
-
E.
oftenBlendedAs
Indicates that two or more entities are frequently mixed or combined together, typically to form a unified product or result.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9d1f2408190beaa8197641c66b4 |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb438c481908dff87c47de2f069 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:07 p.m.