Triple
T22922625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | nasi liwet Sunda |
E568903
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | regional variant of nasi liwet |
C29546
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: regional variant of nasi liwet Context triple: [nasi liwet Sunda, instanceOf, regional variant of nasi liwet]
-
A.
Nasi
chosen
Nasi is a conceptual class representing a rice-based dish, typically cooked or prepared in various styles and often serving as a staple or central component of a meal in many cuisines.
-
B.
regional variety of the Sasak language
A regional variety of the Sasak language is a geographically and socially distinct form of Sasak characterized by systematic differences in pronunciation, vocabulary, and grammar from other Sasak varieties.
-
C.
regional variety of the Javanese language
A regional variety of the Javanese language is a geographically distinct form of Javanese characterized by unique phonological, lexical, and sometimes grammatical features while remaining mutually intelligible with other Javanese varieties.
-
D.
satay dish
A satay dish is a Southeast Asian meal consisting of skewered and grilled pieces of marinated meat, tofu, or vegetables, typically served with a rich, savory peanut sauce and accompaniments like rice cakes and cucumber.
-
E.
Sambal language variety
Sambal language variety is a specific form or dialect of the Sambal language, characterized by distinct phonological, lexical, and grammatical features used by a particular Sambal-speaking community.
- F. None of above.
Provenance (1 batch)
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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
Created at: April 17, 2026, 3:43 p.m.