Triple
T6120425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yao |
E136467
|
entity |
| Predicate | neighboringLanguages |
P16383
|
FINISHED |
| Object | Ngoni |
E145980
|
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: Ngoni | Statement: [Yao, neighboringLanguages, Ngoni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ngoni Context triple: [Yao, neighboringLanguages, Ngoni]
-
A.
Ngoni
chosen
Ngoni is a Bantu language spoken by the Ngoni people of parts of Malawi, Tanzania, Mozambique, and Zambia, reflecting historical migrations from the Zulu region.
-
B.
Ngola
Ngola is an alternative name for the Angolar people, a community of African descent primarily associated with São Tomé and Príncipe.
-
C.
Mbanderu
Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
-
D.
Luba
Luba is a coastal town and important port on the southern part of Bioko Island in Equatorial Guinea.
-
E.
Luba
The Luba are a major Bantu-speaking ethnic group of Central Africa, historically known for the powerful Luba Kingdom centered in what is now the Democratic Republic of the Congo.
- 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_69c0089f851c81909e5e189a617dcff6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05bef8dc08190b917ad7209188c62 |
completed | March 22, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1257153748190947cd80589620f12 |
completed | March 23, 2026, 11:35 a.m. |
Created at: March 22, 2026, 4:14 p.m.