Triple
T8809283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kabiye |
E209614
|
entity |
| Predicate | altName |
P39
|
FINISHED |
| Object | Kabye language |
E267643
|
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: Kabye language | Statement: [Kabiye, altName, Kabye language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kabye language Context triple: [Kabiye, altName, Kabye language]
-
A.
Kabye language
chosen
Kabye language is a Gur language spoken primarily in northern Togo and parts of neighboring West African countries by the Kabye people.
-
B.
Kaba language
The Kaba language is a Central Sudanic language spoken primarily in parts of Chad and the Central African Republic by Kaba ethnic groups.
-
C.
Yemba language
Yemba language is a major Bantu-related Grassfields language spoken primarily by the Bamileke people in western Cameroon.
-
D.
Nyagbo language
The Nyagbo language is a Niger-Congo language spoken by the Nyagbo people in the Volta Region of Ghana, closely related to other Ghana–Togo Mountain languages.
-
E.
Kamba language
Kamba language is a Bantu language spoken primarily by the Kamba people of Kenya, known for its rich oral traditions and close linguistic ties to other Central Kenya Bantu languages.
- 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_69ca8363f3308190a47e3f1ebd51f613 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fd4cbec8190a929d4e60da8ad65 |
completed | March 31, 2026, 11:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6fa0e4308190bd01c2d107c8c02d |
completed | April 3, 2026, 7:43 a.m. |
Created at: March 30, 2026, 6:45 p.m.