Triple
T22879102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronga language |
E567410
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Xitsonga |
—
|
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: Xitsonga | Statement: [Ronga language, closelyRelatedTo, Xitsonga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xitsonga Context triple: [Ronga language, closelyRelatedTo, Xitsonga]
-
A.
Xitsonga
chosen
Xitsonga is a Bantu language spoken primarily by the Tsonga people in southern Africa, notably in South Africa, Mozambique, and Zimbabwe.
-
B.
Siswati
Siswati is a Bantu language of the Nguni group spoken primarily in Eswatini and South Africa, where it holds official status.
-
C.
Tshivenda
Tshivenda is a Bantu language spoken primarily by the Venda people in northern South Africa and neighboring regions.
-
D.
Xhosa
Xhosa is a Bantu language of South Africa, known for its distinctive click consonants and as one of the country’s major official languages.
-
E.
Setswana
Setswana is a Bantu language spoken primarily in Botswana and parts of South Africa, known for being one of the region’s major indigenous languages.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f5a26f4819086ede6d85a2ab2bf |
completed | April 29, 2026, 3:47 a.m. |
Created at: April 17, 2026, 3:39 p.m.