Triple
T8271644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | medronho brandy |
E193441
|
entity |
| Predicate | servingCulture |
P55615
|
FINISHED |
| Object | offered to guests |
—
|
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: offered to guests | Statement: [medronho brandy, servingCulture, offered to guests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servingCulture Context triple: [medronho brandy, servingCulture, offered to guests]
-
A.
servesTradition
chosen
Indicates that one entity upholds, maintains, or performs a tradition for the benefit or continuation of that tradition.
-
B.
traditionalCuisine
Indicates that an entity is associated with the customary or historically rooted style of cooking and food preparation characteristic of a particular culture, region, or community.
-
C.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
D.
cuisine
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
-
E.
servingStyle
Indicates how something (typically food or drink) is presented or offered for consumption or use.
- 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7986f8cc8190a529dda980dd6e98 |
completed | March 31, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69cb70a4525481909399d313a6247ace |
completed | March 31, 2026, 6:58 a.m. |
Created at: March 30, 2026, 5:50 p.m.