Triple
T100714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peru |
E2033
|
entity |
| Predicate | popularDrink |
P4038
|
FINISHED |
| Object | pisco |
—
|
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: pisco | Statement: [Peru, popularDrink, pisco]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularDrink Context triple: [Peru, popularDrink, pisco]
-
A.
traditionalDrink
chosen
Indicates that one entity is a beverage customarily consumed within the culture, heritage, or longstanding practices associated with another entity.
-
B.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
C.
domesticCup
Indicates that an entity has won or participated in a domestic (national-level) cup competition within its sport or domain.
-
D.
popularFor
Indicates that something is widely liked, recognized, or favored specifically because of a particular feature, quality, or use.
-
E.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2563921f8819087f720b1c803579f |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.