Triple
T4797762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pilsner Urquell Brewery |
E106753
|
entity |
| Predicate | usesBrewingMethod |
P53110
|
FINISHED |
| Object | triple decoction mashing |
—
|
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: triple decoction mashing | Statement: [Pilsner Urquell Brewery, usesBrewingMethod, triple decoction mashing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBrewingMethod Context triple: [Pilsner Urquell Brewery, usesBrewingMethod, triple decoction mashing]
-
A.
brewingMethod
chosen
Indicates the technique or process used to brew or prepare a beverage, typically coffee or tea.
-
B.
fermentationMethod
Indicates the process or technique by which a substance is fermented to achieve a desired transformation or product.
-
C.
brewingTime
Indicates the duration required to brew or prepare a beverage or similar concoction.
-
D.
hasCaffeinatedOption
Indicates that something offers or includes at least one option that contains caffeine.
-
E.
teaType
Indicates the specific variety or category of tea associated with an 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6b40c29c8190adab3503f8ba0145 |
completed | March 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69bd622f88188190a51d52ccfad3d2dd |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:22 p.m.