Triple
T38642087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ten High Bourbon |
E938621
|
entity |
| Predicate | alcoholSubType |
P164637
|
FINISHED |
| Object | bourbon |
—
|
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: bourbon | Statement: [Ten High Bourbon, alcoholSubType, bourbon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alcoholSubType Context triple: [Ten High Bourbon, alcoholSubType, bourbon]
-
A.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
-
B.
alcoholicCategory
chosen
Indicates that one entity is classified as a type or category within the domain of alcoholic beverages in relation to another entity.
-
C.
alcoholStrengthCategory
Indicates the classification of an alcoholic beverage based on the strength or concentration of its alcohol content.
-
D.
grainSpiritType
Indicates the specific type or category of spirit distilled from a given grain.
-
E.
madeWithAlcohol
Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
- 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_69f76ed948ec81908ce7811608a8f359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdb0de8c08190928cd1323f80ab5c |
completed | May 7, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69fcd9017dd88190b32a73fe78909740 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:32 p.m.