Triple
T10628925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bouzeron |
E250397
|
entity |
| Predicate | typicalFoodPairings |
P14740
|
FINISHED |
| Object | seafood |
—
|
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: seafood | Statement: [Bouzeron, typicalFoodPairings, seafood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFoodPairings Context triple: [Bouzeron, typicalFoodPairings, seafood]
-
A.
typicalFoodPairing
chosen
Indicates that one food item is commonly served, consumed, or matched together with another as a customary or complementary pairing.
-
B.
relatedCocktail
Indicates that one cocktail has a meaningful connection or association with another cocktail, such as similarity in ingredients, style, or origin.
-
C.
sharesCuisineWith
Indicates that two entities offer or are associated with the same type or style of cuisine.
-
D.
commonCocktail
Indicates that the related entities are ingredients or components that commonly appear together in the same cocktail.
-
E.
traditionalDrink
Indicates that one entity is a beverage customarily consumed within the culture, heritage, or longstanding practices associated with another entity.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df92f8388190a8bcff96809d8eb4 |
completed | April 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69d6dd7fae088190973f70c69738af49 |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 8:59 p.m.