Triple
T12284274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Fashioned |
E292787
|
entity |
| Predicate | bittersType |
P100847
|
FINISHED |
| Object | aromatic bitters |
—
|
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: aromatic bitters | Statement: [Old Fashioned, bittersType, aromatic bitters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bittersType Context triple: [Old Fashioned, bittersType, aromatic bitters]
-
A.
bitterantType
chosen
Indicates the specific kind or category of bitterant used or associated with an entity.
-
B.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
C.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
-
D.
beerStyle
Indicates that one entity is the style or type classification of a beer associated with another entity.
-
E.
distilleryType
Indicates the specific kind or category of distillery associated with an entity (e.g., craft, industrial, micro, or regional type).
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.