Triple
T28771128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uerige brewery |
E726414
|
entity |
| Predicate | styleOfBeer |
P52234
|
FINISHED |
| Object | top-fermented beer |
—
|
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: top-fermented beer | Statement: [Uerige brewery, styleOfBeer, top-fermented beer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: styleOfBeer Context triple: [Uerige brewery, styleOfBeer, top-fermented beer]
-
A.
beerStyle
chosen
Indicates that one entity is the style or type classification of a beer associated with another entity.
-
B.
breweryType
Indicates the specific category or classification of a brewery based on its operational or business characteristics.
-
C.
beerColor
Indicates the color characteristic associated with a particular beer.
-
D.
hasFlagshipBeerCharacteristics
Indicates that one beer possesses the defining qualities or signature traits typically associated with a brewery’s primary or flagship beer.
-
E.
wineStyleContribution
Indicates how much a given factor or component influences or shapes the overall style or character of a wine.
- 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_69f03199997c8190b6ae43fb19312443 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec5bf508190ad088b89455252bd |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 28, 2026, 6:15 a.m.