Triple
T6753798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara language |
E154401
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Kaba languages |
E262847
|
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: Kaba languages | Statement: [Sara language, closelyRelatedTo, Kaba languages]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaba languages Context triple: [Sara language, closelyRelatedTo, Kaba languages]
-
A.
Kaba language
chosen
The Kaba language is a Central Sudanic language spoken primarily in parts of Chad and the Central African Republic by Kaba ethnic groups.
-
B.
Bongo–Bagirmi languages
The Bongo–Bagirmi languages are a subgroup of Central Sudanic languages spoken primarily in South Sudan, Chad, and the Central African Republic.
-
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.
Sabaki languages
The Sabaki languages are a subgroup of Bantu languages spoken along the East African coast and nearby regions, including well-known varieties such as Swahili.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1f32fa08190bb23dc24fef14c8d |
completed | March 27, 2026, 6:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70b1c4594819084716e21b16191e3 |
completed | March 27, 2026, 10:56 p.m. |
Created at: March 27, 2026, 2:11 p.m.