Triple
T38614108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Académie centrafricaine |
E934565
|
entity |
| Predicate | standardizesVocabularyOf |
P195341
|
FINISHED |
| Object | Sango |
—
|
NE NERFINISHED |
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: Sango | Statement: [Académie centrafricaine, standardizesVocabularyOf, Sango]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardizesVocabularyOf Context triple: [Académie centrafricaine, standardizesVocabularyOf, Sango]
-
A.
hasVocabularyFrom
Indicates that one entity’s vocabulary, terminology, or set of terms is derived from, based on, or taken from another entity.
-
B.
isPartOfVocabulary
Indicates that something belongs to or is included within a particular vocabulary or defined set of terms.
-
C.
standardizedFor
Indicates that something has been adjusted or converted to conform to a common standard, format, or reference so it can be consistently compared or used.
-
D.
standardizesOrthographyOf
chosen
Indicates that one entity establishes or applies a consistent writing system or spelling conventions to another entity’s language or text.
-
E.
usesTerminologyFrom
Indicates that one entity adopts or incorporates the specialized terms or vocabulary originating from another entity or source.
- 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_69f76eccd6d081909ccce171011739a1 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fdd07a34c08190982b8c61c2775cf6 |
completed | May 8, 2026, noon |
| PD | Predicate disambiguation | batch_69fdbd25c7908190b72fca8de7ce503f |
completed | May 8, 2026, 10:38 a.m. |
Created at: May 3, 2026, 4:32 p.m.