Triple
T28595793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swahili Wiktionary |
E723766
|
entity |
| Predicate | mainLanguageOfContent |
P31857
|
FINISHED |
| Object | Swahili |
—
|
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: Swahili | Statement: [Swahili Wiktionary, mainLanguageOfContent, Swahili]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainLanguageOfContent Context triple: [Swahili Wiktionary, mainLanguageOfContent, Swahili]
-
A.
contentLanguage
chosen
Indicates the language in which the content is expressed or intended to be understood.
-
B.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
C.
primaryLanguageType
Indicates the main category or kind of language (such as spoken, written, or signed) that serves as the primary mode of communication in a given context or for a given entity.
-
D.
dominantMediaLanguage
Indicates that one language is the primary or most prevalent medium of communication used in a given media context or outlet.
-
E.
canonicalLanguage
Indicates that one entity is the officially recognized or standard language associated with another 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_69f01d80b1908190980594837604b8c7 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f66d7765208190b87b1cc6d96a151c |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 4:21 a.m.