Triple
T33053593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sula Rasa |
E845792
|
entity |
| Predicate | recommendedFoodPairing |
P14740
|
FINISHED |
| Object | grilled meats |
—
|
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: grilled meats | Statement: [Sula Rasa, recommendedFoodPairing, grilled meats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recommendedFoodPairing Context triple: [Sula Rasa, recommendedFoodPairing, grilled meats]
-
A.
typicalFoodPairing
chosen
Indicates that one food item is commonly served, consumed, or matched together with another as a customary or complementary pairing.
-
B.
winePairing
Indicates a relationship where a particular wine is recommended as a suitable accompaniment for a given food or dish.
-
C.
offersWinePairing
Indicates that one entity provides or suggests a complementary wine selection to accompany another entity, such as a dish, meal, or menu.
-
D.
wineServingSuggestion
Indicates the recommended way or context in which a particular wine is best served or enjoyed.
-
E.
drinksWith
Indicates that two entities consume beverages together, typically at the same time and place in a social context.
- 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_69f3495242e48190996a2cb2beab5455 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:24 a.m.