Triple
T26202892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apma people |
E655278
|
entity |
| Predicate | useOfBislama |
P108903
|
FINISHED |
| Object | lingua franca in Vanuatu |
—
|
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: lingua franca in Vanuatu | Statement: [Apma people, useOfBislama, lingua franca in Vanuatu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: useOfBislama Context triple: [Apma people, useOfBislama, lingua franca in Vanuatu]
-
A.
isPapuanLanguage
Indicates that a language belongs to the group of Papuan languages, typically indigenous to New Guinea and surrounding regions.
-
B.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
C.
usesSlangFrom
Indicates that one entity incorporates or employs slang expressions originating from another entity or source.
-
D.
usesLanguageFor
chosen
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
E.
hasSlang
Indicates that one entity is an informal, colloquial, or slang term referring to the other 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_69ee5b48236c81908fe385b6afc4f60b |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60cdc6c9481909f9e9ba371a1a329 |
completed | May 2, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69f5b007ec1c819092e2c3605933f60b |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 26, 2026, 8:49 p.m.