Triple
T6293699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbecue Capital of the World |
E141079
|
entity |
| Predicate | hasMainMeat |
P51949
|
FINISHED |
| Object | pork |
—
|
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 | Statement: [Barbecue Capital of the World, hasMainMeat, pork]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainMeat Context triple: [Barbecue Capital of the World, hasMainMeat, pork]
-
A.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
B.
meatType
chosen
Indicates the specific category or kind of meat associated with an entity.
-
C.
typicalMeat
Indicates that something is commonly or characteristically used or regarded as meat in a given context.
-
D.
isNonVegetarian
Indicates that an entity consumes or includes meat or animal-based products, and therefore does not follow a vegetarian diet.
-
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_69c008cdf2ac8190bb640c94478fb4ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06438654481908c9833c5f0d61773 |
completed | March 22, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69c060df0d8881908215575862ef6831 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:27 p.m.