Triple
T8714475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oktoberfestbier |
E206859
|
entity |
| Predicate | bitternessRangeIBU |
P38317
|
FINISHED |
| Object | 18–25 IBU |
—
|
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: 18–25 IBU | Statement: [Oktoberfestbier, bitternessRangeIBU, 18–25 IBU]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bitternessRangeIBU Context triple: [Oktoberfestbier, bitternessRangeIBU, 18–25 IBU]
-
A.
hasBitternessLevel
chosen
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
B.
bottlingStrengthRange
Indicates the range of alcohol strengths at which a beverage is bottled.
-
C.
hasPeatingLevelRange
Indicates that something is associated with a specified range of peatiness levels, typically expressing how peated or smoky it is within defined minimum and maximum bounds.
-
D.
minimumBottlingStrength
Indicates the lowest alcohol strength at which a beverage is allowed or intended to be bottled.
-
E.
brewingTemperature
Indicates the specific temperature at which a brewing process is carried out.
- 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_69ca83572d4881909bef3be2b578d539 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5cd6707c819092c9fca34f273d5e |
completed | March 31, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69cc456e806c819087e7d66ee737f242 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:35 p.m.