Triple
T6293706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbecue Capital of the World |
E141079
|
entity |
| Predicate | hasTypicalSide |
P70748
|
FINISHED |
| Object | red slaw |
—
|
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: red slaw | Statement: [Barbecue Capital of the World, hasTypicalSide, red slaw]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalSide Context triple: [Barbecue Capital of the World, hasTypicalSide, red slaw]
-
A.
hasSeriousSideEffect
Indicates that an entity (such as a treatment, drug, or intervention) causes or is associated with a significant or severe adverse effect on another entity (typically a patient or biological system).
-
B.
hasBside
Indicates that one item serves as the B-side counterpart or secondary track associated with another primary item, typically in a recording or media release.
-
C.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
-
D.
hasSideEvent
Indicates that an event is associated with an additional, related side event occurring alongside it.
-
E.
hasCommonAdverseEffect
Indicates that two or more entities share at least one adverse effect that occurs in response to them.
- 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_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. |
| PDg | Predicate description generation | batch_69c06284848c8190a0151ff3e8682889 |
completed | March 22, 2026, 9:43 p.m. |
Created at: March 22, 2026, 4:27 p.m.