Triple
T1233877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington, North Carolina |
E26503
|
entity |
| Predicate | barbecueStyle |
P17157
|
FINISHED |
| Object | pork shoulder with vinegar-based red 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: pork shoulder with vinegar-based red sauce | Statement: [Lexington, North Carolina, barbecueStyle, pork shoulder with vinegar-based red sauce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: barbecueStyle Context triple: [Lexington, North Carolina, barbecueStyle, pork shoulder with vinegar-based red sauce]
-
A.
smokedOver
Indicates that one entity smoked (used tobacco or similar substances) for a duration exceeding a specified time or threshold.
-
B.
servingStyle
Indicates how something (typically food or drink) is presented or offered for consumption or use.
-
C.
diningStyle
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
D.
cuisineFeature
chosen
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
E.
feastType
Indicates the specific kind or category of feast associated with an event or occasion.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be5d16ec819088056167c88d3318 |
completed | March 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69a4bb65d61c8190bf0424ea0019a98b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.