Triple
T5193051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Memphis-style barbecue |
E117201
|
entity |
| Predicate | sauceStyle |
P51950
|
FINISHED |
| Object | tomato-based barbecue sauce |
—
|
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: tomato-based barbecue sauce | Statement: [Memphis-style barbecue, sauceStyle, tomato-based barbecue sauce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sauceStyle Context triple: [Memphis-style barbecue, sauceStyle, tomato-based barbecue sauce]
-
A.
sauceType
chosen
Indicates the specific kind or category of sauce associated with an item or dish.
-
B.
typicalSauceConsistency
Indicates that something has the usual or characteristic thickness or texture expected of a sauce.
-
C.
isTypicallyGarnishedWith
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
D.
servingStyle
Indicates how something (typically food or drink) is presented or offered for consumption or use.
-
E.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
- 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.