Triple
T7519392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marsannay |
E177727
|
entity |
| Predicate | typicalServingTemperatureRosé |
P66977
|
FINISHED |
| Object | around 10–12 °C |
—
|
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: around 10–12 °C | Statement: [Marsannay, typicalServingTemperatureRosé, around 10–12 °C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalServingTemperatureRosé Context triple: [Marsannay, typicalServingTemperatureRosé, around 10–12 °C]
-
A.
wineServingTemperature
Indicates the temperature at which a particular wine is or should be served.
-
B.
recommendedServingTemperature
chosen
Indicates the temperature at which something (typically food or drink) is advised to be served for optimal use or enjoyment.
-
C.
roséWineAllowed
Indicates that the consumption or presence of rosé wine is permitted in the given context or under the specified conditions.
-
D.
wineServingSuggestion
Indicates the recommended way or context in which a particular wine is best served or enjoyed.
-
E.
wineColor
Indicates the color attribute or hue associated with a given wine.
- 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_69c69f2891148190a484f3b8222c6f1b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5f98ae48190946a18d7c2d33bcd |
completed | March 27, 2026, 9:26 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d6bb808190bdd04499fd3bceb6 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:46 p.m.