Triple
T19918128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beukes |
E478717
|
entity |
| Predicate | languageOfOrigin |
P151
|
FINISHED |
| Object | Afrikaans |
—
|
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: Afrikaans | Statement: [Beukes, languageOfOrigin, Afrikaans]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Afrikaans Context triple: [Beukes, languageOfOrigin, Afrikaans]
-
A.
Afrikaans
chosen
Afrikaans is a West Germanic language spoken mainly in South Africa and Namibia, originating from 17th-century Dutch and influenced by various African and Asian languages.
-
B.
Siswati
Siswati is a Bantu language of the Nguni group spoken primarily in Eswatini and South Africa, where it holds official status.
-
C.
Afrikaansche Galey
Afrikaansche Galey was a Dutch exploration ship notably associated with the early 18th-century Pacific voyages of navigator Jacob Roggeveen.
-
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.
Tshivenda
Tshivenda is a Bantu language spoken primarily by the Venda people in northern South Africa and neighboring regions.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c3d990819089386d9f30323e8c |
completed | April 20, 2026, 4:52 p.m. |
Created at: April 10, 2026, 1:53 p.m.