Triple
T6293822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington Barbecue Festival |
E141081
|
entity |
| Predicate | hasBeverageCategory |
P70752
|
FINISHED |
| Object | soft drinks |
—
|
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: soft drinks | Statement: [Lexington Barbecue Festival, hasBeverageCategory, soft drinks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeverageCategory Context triple: [Lexington Barbecue Festival, hasBeverageCategory, soft drinks]
-
A.
beverageSubcategory
Indicates a more specific classification within a broader beverage category, defining the subtype or subcategory of a drink.
-
B.
hasCaffeinatedOption
Indicates that something offers or includes at least one option that contains caffeine.
-
C.
hasCaffeineContent
Indicates that one entity (typically a beverage or substance) possesses a specified amount or presence of caffeine.
-
D.
hasBeverageProgram
Indicates that an entity offers, manages, or participates in an organized beverage-related offering or initiative.
-
E.
isPackagedBeverage
Indicates that an item is a beverage that has been contained or sealed within some form of packaging for distribution or consumption.
- 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.