Triple
T28955088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schumacher brewery |
E731136
|
entity |
| Predicate | alcoholicBeverage |
P164637
|
FINISHED |
| Object | Altbier |
—
|
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: Altbier | Statement: [Schumacher brewery, alcoholicBeverage, Altbier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alcoholicBeverage Context triple: [Schumacher brewery, alcoholicBeverage, Altbier]
-
A.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
-
B.
madeWithAlcohol
Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
-
C.
isAlcoholicBeverage
Indicates that a beverage contains alcohol and is classified as an alcoholic drink.
-
D.
alcoholicCategory
chosen
Indicates that one entity is classified as a type or category within the domain of alcoholic beverages in relation to another entity.
-
E.
drinkFamily
Indicates a familial or close relational connection between two entities centered around drinking-related activities or contexts.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65bbb6c088190a98b23cef5a3a503 |
completed | May 2, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 8:46 a.m.