Triple
T16716944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andechser Doppelbock Dunkel |
E406247
|
entity |
| Predicate | maltProfile |
P69349
|
FINISHED |
| Object | rich malt character |
—
|
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: rich malt character | Statement: [Andechser Doppelbock Dunkel, maltProfile, rich malt character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maltProfile Context triple: [Andechser Doppelbock Dunkel, maltProfile, rich malt character]
-
A.
typeOfMalt
Indicates the specific kind or category of malt used or referenced in relation to another entity.
-
B.
hasTastingProfile
chosen
Indicates that an entity possesses a specific flavor or sensory profile, typically describing its characteristic tastes and aromas.
-
C.
palateProfile
Indicates the characteristic taste and flavor qualities associated with something, such as a food or beverage.
-
D.
roastProfile
Indicates the specific roasting characteristics or level applied to an item (typically coffee), defining how it was roasted.
-
E.
hasProfile
Indicates that an entity is associated with or possesses a specific profile representation or account.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e38656b66081909f2c2a8971c45aee |
completed | April 18, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.