Triple
T11310915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black South African |
E267831
|
entity |
| Predicate | hasEthnicSubgroup |
P14193
|
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: [Black South African, hasEthnicSubgroup, Tsonga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsonga Context triple: [Black South African, hasEthnicSubgroup, 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.
Wedza
Wedza is a rural district and township in northeastern Zimbabwe known for its agriculture and gold deposits.
-
D.
Chambeali
Chambeali is an Indo-Aryan language spoken primarily in the Chamba region of Himachal Pradesh in northern India.
-
E.
Baganga
Baganga is a coastal municipality in the province of Davao Oriental in the Philippines, known for its beaches, waterfalls, and rich marine and forest resources.
- 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_69d6aaca5c24819083db46a30d86cb34 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9c0b3b88190ac0e3d6a5ad3b9bc |
completed | April 9, 2026, 6:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a7fc06881909afe85a600d25ff2 |
completed | April 19, 2026, 5:01 p.m. |
Created at: April 8, 2026, 9:32 p.m.