Triple
T25637599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corona Premier |
E642747
|
entity |
| Predicate | recommendedServing |
P66977
|
FINISHED |
| Object | served cold |
—
|
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: served cold | Statement: [Corona Premier, recommendedServing, served cold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recommendedServing Context triple: [Corona Premier, recommendedServing, served cold]
-
A.
marketedAsServing
Indicates that something is promoted or advertised as providing service to a particular audience, purpose, or function.
-
B.
servingSuggestionRed
Indicates that something is recommended or suggested to be served together with a red wine.
-
C.
recommendedPreparation
Indicates that one entity is suggested or advised as a suitable preparation or prerequisite for engaging with another entity.
-
D.
traditionallyServed
Indicates that one entity is customarily or conventionally presented, offered, or consumed together with another entity.
-
E.
recommendedServingTemperature
chosen
Indicates the temperature at which something (typically food or drink) is advised to be served for optimal use or enjoyment.
- 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_69e77e7ce28081908b08d65ee6e5c8be |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fa6345548190a52498ecb0a2f555 |
completed | May 2, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 5:34 p.m.