Triple
T37625581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry McKenna Single Barrel 10 Year |
E936196
|
entity |
| Predicate | grainComponent |
P32631
|
FINISHED |
| Object | corn (majority of mash bill) |
—
|
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: corn (majority of mash bill) | Statement: [Henry McKenna Single Barrel 10 Year, grainComponent, corn (majority of mash bill)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grainComponent Context triple: [Henry McKenna Single Barrel 10 Year, grainComponent, corn (majority of mash bill)]
-
A.
grain
Indicates that one entity is composed of or contains a granular substance or small particles of another entity.
-
B.
grainShape
Indicates the characteristic form or contour of a grain or granular particle.
-
C.
hasGrainType
chosen
Indicates that an entity is characterized by or associated with a specific type of grain.
-
D.
granaryType
Indicates the specific kind or category of granary associated with or used by an entity.
-
E.
hasGrainQuality
Indicates that an entity possesses a particular level or type of grain quality, characterizing the quality attributes of its grain.
- 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_69f76ed24820819081bafd36e9088701 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.