Triple
T9826561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rully |
E238667
|
entity |
| Predicate | foodPairingRed |
P14740
|
FINISHED |
| Object | roast poultry |
—
|
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: roast poultry | Statement: [Rully, foodPairingRed, roast poultry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foodPairingRed Context triple: [Rully, foodPairingRed, roast poultry]
-
A.
typicalFoodPairing
chosen
Indicates that one food item is commonly served, consumed, or matched together with another as a customary or complementary pairing.
-
B.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
C.
favoriteFood
Indicates that one entity has a preferred or most liked food item in relation to another entity or context.
-
D.
similarDish
Indicates that two dishes share notable similarities, such as ingredients, preparation methods, flavor profile, or style.
-
E.
sharesCuisineWith
Indicates that two entities offer or are associated with the same type or style of cuisine.
- 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_69ca84e0dd1881909800765d1e21f735 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb32370e8819087c85fb8328587be |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.