Triple
T6809841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolcetto |
E156601
|
entity |
| Predicate | drinkingWindowStyle |
P73208
|
FINISHED |
| Object | early-drinking |
—
|
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: early-drinking | Statement: [Dolcetto, drinkingWindowStyle, early-drinking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drinkingWindowStyle Context triple: [Dolcetto, drinkingWindowStyle, early-drinking]
-
A.
drinkingPermitted
Indicates that consuming alcoholic beverages is allowed in a given context, location, or situation.
-
B.
allowsTastingOf
Indicates that one entity permits another entity to sample or try the taste of something.
-
C.
signatureDrink
Indicates that a particular drink is the characteristic or specially associated beverage of an entity (such as a person, venue, or brand).
-
D.
windowType
Indicates the specific kind or category of window associated with an entity.
-
E.
drunkWith
Indicates that one entity is intoxicated as a result of consuming a particular alcoholic beverage or substance associated with another entity.
- 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d30c741881909e220b05aa564bc2 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d1d5f1908190989efc8a2d18c965 |
completed | March 27, 2026, 6:52 p.m. |
Created at: March 27, 2026, 2:16 p.m.