Triple
T4159122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krio language |
E91486
|
entity |
| Predicate | hasInfluenceFrom |
P9
|
FINISHED |
| Object | Kongo languages |
E57354
|
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: Kongo languages | Statement: [Krio language, hasInfluenceFrom, Kongo languages]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kongo languages Context triple: [Krio language, hasInfluenceFrom, Kongo languages]
-
A.
Luba languages
The Luba languages are a group of closely related Bantu languages spoken primarily in the Democratic Republic of the Congo by the Luba people and neighboring communities.
-
B.
Sena–Nyanja languages
The Sena–Nyanja languages are a group of closely related Bantu languages spoken primarily in parts of Malawi, Mozambique, and neighboring regions of southeastern Africa.
-
C.
Teke–Mbede languages
The Teke–Mbede languages are a group of closely related Bantu languages spoken primarily in Gabon and neighboring Central African countries.
-
D.
Bena–Mboi languages
The Bena–Mboi languages are a small group of closely related Niger–Congo languages spoken primarily in northeastern Nigeria.
-
E.
Kikongo
chosen
Kikongo is a Bantu language widely spoken in Central Africa, particularly in the western regions of the Democratic Republic of the Congo and neighboring countries.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0292baf88190a51156b63672ae38 |
completed | March 9, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f40678481908894ff315932a610 |
completed | March 14, 2026, 3:31 p.m. |
Created at: March 9, 2026, 3:44 p.m.