Triple
T31754599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico Pavilion at EPCOT |
E810523
|
entity |
| Predicate | hasBeverageSpecialty |
P180542
|
FINISHED |
| Object | tequila |
—
|
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: tequila | Statement: [Mexico Pavilion at EPCOT, hasBeverageSpecialty, tequila]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeverageSpecialty Context triple: [Mexico Pavilion at EPCOT, hasBeverageSpecialty, tequila]
-
A.
hasBeverageCategory
Indicates that an entity is associated with or classified under a particular beverage category.
-
B.
hasBeverageProduct
chosen
Indicates that one entity possesses, offers, or is associated with a particular beverage product.
-
C.
hasBeverageReference
Indicates that one entity makes reference to, mentions, or is associated with a beverage in some way.
-
D.
beverageSubcategory
Indicates a more specific classification within a broader beverage category, defining the subtype or subcategory of a drink.
-
E.
hasCaffeinatedOption
Indicates that something offers or includes at least one option that contains caffeine.
- 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_69f348e340d48190b780fae618c51464 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 30, 2026, 11:29 p.m.