Triple
T28164979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bönnsch |
E715000
|
entity |
| Predicate | hasProductionMethodSimilarTo |
P197698
|
FINISHED |
| Object | Kölsch brewing tradition |
—
|
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: Kölsch brewing tradition | Statement: [Bönnsch, hasProductionMethodSimilarTo, Kölsch brewing tradition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProductionMethodSimilarTo Context triple: [Bönnsch, hasProductionMethodSimilarTo, Kölsch brewing tradition]
-
A.
hasProductionMethod
Indicates that one entity is produced, created, or manufactured using the method, process, or technique specified by another entity.
-
B.
isProducedFrom
Indicates that something is created, generated, or derived from a specified source or input.
-
C.
hasProduction
Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
-
D.
inUniverseProductionMethod
Indicates that a work’s method of production is depicted as occurring within the fictional universe itself, rather than only in the real-world creation process.
-
E.
usesProductionModel
Indicates that one entity employs or relies on another entity as its primary or official production model in practice.
- 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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69fea2d0a4d08190aa06aeb902a02d5a |
completed | May 9, 2026, 2:58 a.m. |
| PD | Predicate disambiguation | batch_69fea24698348190b9b992a8e7cdbcd0 |
completed | May 9, 2026, 2:56 a.m. |
| PDg | Predicate description generation | batch_69fea2cfcd648190a15e5b90889095b1 |
completed | May 9, 2026, 2:58 a.m. |
Created at: April 27, 2026, 10:09 p.m.