Triple
T978283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kansas City–style barbecue |
E21106
|
entity |
| Predicate | typicalMeat |
P22120
|
FINISHED |
| Object | pork ribs |
—
|
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: pork ribs | Statement: [Kansas City–style barbecue, typicalMeat, pork ribs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalMeat Context triple: [Kansas City–style barbecue, typicalMeat, pork ribs]
-
A.
commonMeatCut
Indicates that two items are the same or equivalent cut of meat, or that an item belongs to a standard, commonly recognized meat cut category.
-
B.
sacrificeAnimalType
Indicates that an entity performs or is involved in the act of sacrificing an animal of a specified type.
-
C.
primaryFood
Indicates that one entity serves as the main or most important food source for another entity.
-
D.
meatDistributionRule
Indicates the rule or policy that governs how meat is allocated, portioned, or distributed among recipients or locations.
-
E.
feastType
Indicates the specific kind or category of feast associated with an event or occasion.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69a4b344f6f48190ba03ce593c94176b |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.