Triple
T2582692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ekurhuleni |
E57128
|
entity |
| Predicate | officialLanguage |
P236
|
FINISHED |
| Object | Tsonga |
E70172
|
NE 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: Tsonga | Statement: [Ekurhuleni, officialLanguage, Tsonga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsonga Context triple: [Ekurhuleni, officialLanguage, Tsonga]
-
A.
Tsonga
chosen
Tsonga is a Bantu language spoken primarily in southern Africa, especially in Mozambique and South Africa, by the Tsonga (Xitsonga) people.
-
B.
Marakwet
Marakwet is a Southern Nilotic language spoken primarily by the Marakwet people of Kenya’s Rift Valley region.
-
C.
Sanglechi
Sanglechi is a lesser-known Eastern Iranian language spoken in parts of northeastern Afghanistan and adjacent regions.
-
D.
Chambo
Chambo is a small town in central Ecuador known for its agricultural activities and proximity to the Andean highlands.
-
E.
Tangara
Tangara is a genus of brightly colored Neotropical tanagers known for their diverse plumage patterns and widespread presence in Central and South American forests.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3c9d0548190b29743ac1d7837ff |
completed | March 7, 2026, 7:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af657cc2b08190a9055d6da7744851 |
completed | March 10, 2026, 12:27 a.m. |
Created at: March 6, 2026, 9:49 p.m.