Triple
T8714470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oktoberfestbier |
E206859
|
entity |
| Predicate | colorScaleSRM |
P84041
|
FINISHED |
| Object | 4–7 SRM (modern festbier versions) |
—
|
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: 4–7 SRM (modern festbier versions) | Statement: [Oktoberfestbier, colorScaleSRM, 4–7 SRM (modern festbier versions)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorScaleSRM Context triple: [Oktoberfestbier, colorScaleSRM, 4–7 SRM (modern festbier versions)]
-
A.
colorGrade
Indicates the qualitative or categorical assessment of an entity’s color according to a defined grading scale.
-
B.
colorOfLiquor
Indicates the specific color or hue that a given liquor possesses.
-
C.
liquorColor
Indicates the characteristic color or hue associated with a particular liquor.
-
D.
capeColor
Indicates the color attribute associated with a cape worn or possessed by an entity.
-
E.
grapeColorDistribution
Indicates how colors are proportionally or categorically distributed among a set of grapes.
- 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_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. |
| PDg | Predicate description generation | batch_69cc46c40c54819093d174a4203f9515 |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:35 p.m.