Triple
T14373032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glenmorangie |
E356401
|
entity |
| Predicate | usesMashTun |
P69350
|
FINISHED |
| Object | traditional mash tun |
—
|
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: traditional mash tun | Statement: [Glenmorangie, usesMashTun, traditional mash tun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMashTun Context triple: [Glenmorangie, usesMashTun, traditional mash tun]
-
A.
hasMashTunType
chosen
Indicates that an entity is associated with or uses a specific type or configuration of mash tun.
-
B.
hasMashBill
Indicates that an alcoholic beverage (typically a spirit like whiskey or bourbon) is produced using a specific mixture of grains (the mash bill).
-
C.
typeOfMalt
Indicates the specific kind or category of malt used or referenced in relation to another entity.
-
D.
isMixedBeer
Indicates that a beer is composed by mixing two or more different beers together.
-
E.
mustBeFermentedBy
Indicates that one entity is required to undergo a fermentation process carried out by another specified entity.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9007184c8190aebb003cb6548cc8 |
completed | April 14, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:15 a.m.