Triple
T5193057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Memphis-style barbecue |
E117201
|
entity |
| Predicate | typicalRibCut |
P10566
|
FINISHED |
| Object | spare 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: spare ribs | Statement: [Memphis-style barbecue, typicalRibCut, spare ribs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRibCut Context triple: [Memphis-style barbecue, typicalRibCut, spare ribs]
-
A.
commonMeatCut
chosen
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.
typicalMeat
Indicates that something is commonly or characteristically used or regarded as meat in a given context.
-
C.
hasRibs
Indicates that one entity possesses ribs as anatomical structures.
-
D.
meatType
Indicates the specific category or kind of meat associated with an entity.
-
E.
notableMeatProduct
Indicates that one entity is a meat-based product that is especially prominent, well-known, or significant in relation to the other 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_69bd4462ed04819084fcb01eb9d2fa74 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79efd16c8190b0b16278a00baecd |
completed | March 20, 2026, 4:46 p.m. |
| PD | Predicate disambiguation | batch_69bd77b7e8b4819092ec3965e11f2dea |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:46 p.m.