Triple
T1187836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Bantu |
E25286
|
entity |
| Predicate | hasMemberLanguage |
P7390
|
FINISHED |
| Object |
Ndau
Ndau is a Southern Bantu language spoken primarily in central Mozambique and eastern Zimbabwe, closely related to Shona.
|
E147443
|
NE FINISHED |
How this triple was built (4 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: Ndau | Statement: [Southern Bantu, hasMemberLanguage, Ndau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ndau Context triple: [Southern Bantu, hasMemberLanguage, Ndau]
-
A.
Ndowe
Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
-
B.
Nyanda
Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
-
C.
Ngoni
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.
-
D.
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
-
E.
Ewondo
Ewondo is a Bantu language spoken primarily by the Ewondo people in central Cameroon, including in and around the capital city, Yaoundé.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ndau Triple: [Southern Bantu, hasMemberLanguage, Ndau]
Generated description
Ndau is a Southern Bantu language spoken primarily in central Mozambique and eastern Zimbabwe, closely related to Shona.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ndau Target entity description: Ndau is a Southern Bantu language spoken primarily in central Mozambique and eastern Zimbabwe, closely related to Shona.
-
A.
Ndowe
Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
-
B.
Nyanda
Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
-
C.
Ngoni
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.
-
D.
Kumba
Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
-
E.
Ewondo
Ewondo is a Bantu language spoken primarily by the Ewondo people in central Cameroon, including in and around the capital city, Yaoundé.
- F. None of above. chosen
Provenance (5 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd568cf481908d10cf19a3ce28f3 |
completed | March 1, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acacaf11588190b0bbc1d280bf9a78 |
completed | March 7, 2026, 10:54 p.m. |
| NEDg | Description generation | batch_69acad0b6a20819091cfc47b00a81930 |
completed | March 7, 2026, 10:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69acada08c248190904b0934a1e4074a |
completed | March 7, 2026, 10:58 p.m. |
Created at: March 1, 2026, 7:45 p.m.