Triple
T32982852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sidama people |
E843849
|
entity |
| Predicate | haveTraditionalDrink |
P4038
|
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: [Sidama people, haveTraditionalDrink, coffee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveTraditionalDrink Context triple: [Sidama people, haveTraditionalDrink, coffee]
-
A.
traditionalDrink
chosen
Indicates that one entity is a beverage customarily consumed within the culture, heritage, or longstanding practices associated with another entity.
-
B.
hasDrinkNamedAfter
Indicates that one entity has a beverage that is named after another entity.
-
C.
hasMainAlcoholicBeverage
Indicates that one entity is the primary alcoholic beverage associated with, served by, or featured in another entity.
-
D.
hasWineMakingTradition
Indicates that a place or group has an established, culturally recognized history and practice of producing wine.
-
E.
hasBeverageCategory
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_69f3494c6f9c8190a255409fce8b1d3b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:22 a.m.