Triple
T16189278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Setit River area |
E392890
|
entity |
| Predicate | linguisticFamilyContext |
P23832
|
FINISHED |
| Object | Nilo-Saharan languages |
—
|
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: Nilo-Saharan languages | Statement: [Setit River area, linguisticFamilyContext, Nilo-Saharan languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguisticFamilyContext Context triple: [Setit River area, linguisticFamilyContext, Nilo-Saharan languages]
-
A.
languageFamilyContext
chosen
Indicates the broader linguistic family or grouping within which a particular language or linguistic element is situated.
-
B.
shareLanguageFamilyContext
Indicates that two entities are associated with languages that belong to the same language family or broader linguistic grouping within a given context.
-
C.
languageFamily
Indicates that two or more languages belong to the same genealogical language family or linguistic lineage.
-
D.
inLanguageFamily
Indicates that two languages belong to the same linguistic family or classification.
-
E.
languageFamilyOf
Indicates that one entity is the language family to which the other entity (a specific language) belongs.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e222d3a8e48190bdf29a633f4b0490 |
completed | April 17, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69e219e11f6081909106b1240a17fd37 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.