Triple
T4087118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scotch whisky |
E87613
|
entity |
| Predicate | maximumDistillationStrength |
P52921
|
FINISHED |
| Object | 94.8% ABV |
—
|
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: 94.8% ABV | Statement: [Scotch whisky, maximumDistillationStrength, 94.8% ABV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumDistillationStrength Context triple: [Scotch whisky, maximumDistillationStrength, 94.8% ABV]
-
A.
hasDistillery
Indicates that one entity owns, operates, or is associated with a distillery as a facility or production site.
-
B.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
C.
hasHigherSalinityThan
Indicates that one entity has a greater concentration of dissolved salts than another entity.
-
D.
tanninLevel
Indicates the degree or intensity of tannins present in or associated with something, typically a beverage like wine or tea.
-
E.
maximumDraft
Indicates that there is an upper limit on the number of drafts that can be created, stored, or associated with a given entity or process.
- F. None of above. chosen
Provenance (4 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefc7ceeb48190807f0f5078ccfa12 |
completed | March 9, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69aef909c9c88190b09d48dad325a83c |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aef9b34dec81909bbc3def9decc71a |
completed | March 9, 2026, 4:47 p.m. |
Created at: March 9, 2026, 3:39 p.m.