Triple
T16991191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riva promenade |
E412196
|
entity |
| Predicate | typicalBeverageServed |
P70752
|
FINISHED |
| Object | coffee |
—
|
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: coffee | Statement: [Riva promenade, typicalBeverageServed, coffee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBeverageServed Context triple: [Riva promenade, typicalBeverageServed, coffee]
-
A.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
-
B.
traditionalDrink
Indicates that one entity is a beverage customarily consumed within the culture, heritage, or longstanding practices associated with another entity.
-
C.
isTypicallyServedIn
Indicates that something (such as a food or drink) is most commonly or customarily presented or contained within a particular type of vessel or container.
-
D.
beverageSubcategory
Indicates a more specific classification within a broader beverage category, defining the subtype or subcategory of a drink.
-
E.
hasBeverageCategory
chosen
Indicates that an entity is associated with or classified under a particular beverage category.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d280e3348190a27bd5dc7cf87c0e |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.