Triple
T978308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kansas City–style barbecue |
E21106
|
entity |
| Predicate | relatedDish |
P19483
|
FINISHED |
| Object | burnt ends sandwich |
—
|
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: burnt ends sandwich | Statement: [Kansas City–style barbecue, relatedDish, burnt ends sandwich]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedDish Context triple: [Kansas City–style barbecue, relatedDish, burnt ends sandwich]
-
A.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
B.
traditionalDish
chosen
Indicates that the object is a dish customarily prepared, eaten, or recognized within the subject’s cultural or regional tradition.
-
C.
alsoServes
Indicates that an entity, in addition to its primary role or function, provides service or support to another specified entity or group.
-
D.
typicalFoodPairing
Indicates that one food item is commonly served, consumed, or matched together with another as a customary or complementary pairing.
-
E.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b47861808190be56a7bbd926e658 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a8a3b08190b4538e119b13f7f5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:40 p.m.