Triple
T38617701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leinenkugel’s Watermelon Shandy |
E936776
|
entity |
| Predicate | intendedDrinkers |
P13636
|
FINISHED |
| Object | adult consumers |
—
|
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: adult consumers | Statement: [Leinenkugel’s Watermelon Shandy, intendedDrinkers, adult consumers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedDrinkers Context triple: [Leinenkugel’s Watermelon Shandy, intendedDrinkers, adult consumers]
-
A.
effectOnDrinkers
Indicates the impact or consequences that something has on individuals who consume alcoholic beverages.
-
B.
drinksWith
Indicates that two entities consume beverages together, typically at the same time and place in a social context.
-
C.
drinkingWindowCharacteristic
Indicates the typical period or conditions under which a beverage (usually wine) is considered optimal for drinking.
-
D.
drinkingPermitted
Indicates that consuming alcoholic beverages is allowed in a given context, location, or situation.
-
E.
drinksLegalAge
chosen
Indicates that an entity has reached the minimum legal age required to consume alcoholic beverages.
- 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_69f76ed403208190b862dc795171353f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe7eb4b8348190bb19d35766189ed4 |
completed | May 9, 2026, 12:24 a.m. |
| PD | Predicate disambiguation | batch_69fe7c35d2148190ab952e54feda1e76 |
completed | May 9, 2026, 12:13 a.m. |
Created at: May 3, 2026, 4:32 p.m.