Triple
T15325590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waggon and Horses public house |
E366400
|
entity |
| Predicate | typicalBeverageType |
P4038
|
FINISHED |
| Object | beer |
—
|
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: beer | Statement: [Waggon and Horses public house, typicalBeverageType, beer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBeverageType Context triple: [Waggon and Horses public house, typicalBeverageType, beer]
-
A.
beverageSubcategory
Indicates a more specific classification within a broader beverage category, defining the subtype or subcategory of a drink.
-
B.
traditionalDrink
chosen
Indicates that one entity is a beverage customarily consumed within the culture, heritage, or longstanding practices associated with another entity.
-
C.
drinks
Indicates that one entity consumes a liquid substance, typically by ingesting it through the mouth.
-
D.
drinkFamily
Indicates a familial or close relational connection between two entities centered around drinking-related activities or contexts.
-
E.
favoriteDrink
Indicates that one entity has a preferred beverage over others.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dfd8f048190831b463a2728eafe |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca9659f48190b8661df223ce5078 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:16 a.m.