Triple
T31138556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Bush |
E793714
|
entity |
| Predicate | maltContent |
P171189
|
FINISHED |
| Object | high malt content |
—
|
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: high malt content | Statement: [Black Bush, maltContent, high malt content]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maltContent Context triple: [Black Bush, maltContent, high malt content]
-
A.
typeOfMalt
Indicates the specific kind or category of malt used or referenced in relation to another entity.
-
B.
maltingsSupply
Indicates that one entity supplies maltings (facilities or products related to malting) to another entity.
-
C.
hasAlcoholContent
Indicates that an entity contains alcohol and specifies the amount or concentration of that alcohol.
-
D.
madeWithAlcohol
Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
-
E.
alcoholContentRelativeTo
Indicates that the alcohol content of one entity is compared to or expressed in relation to the alcohol content of another entity.
- 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_69f224d2b3a48190aa9dd26fbf6eab1a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c6f01e881908fa84f5d429d37ae |
completed | May 3, 2026, 12:53 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f69c2127088190ae92c72461576d3b |
completed | May 3, 2026, 12:51 a.m. |
Created at: April 29, 2026, 9:05 p.m.