Triple
T15945506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kambaata language |
E386672
|
entity |
| Predicate | glottologName |
P6521
|
FINISHED |
| Object | Kambaata |
E837598
|
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: Kambaata | Statement: [Kambaata language, glottologName, Kambaata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kambaata Context triple: [Kambaata language, glottologName, Kambaata]
-
A.
Kambaata
chosen
Kambaata is a Cushitic language spoken primarily by the Kambaata people in southern Ethiopia.
-
B.
Kamba
Kamba is a Bantu language spoken primarily by the Akamba people of Kenya, known for its rich oral traditions and regional cultural significance.
-
C.
Kambalda
Kambalda is a mining town in Western Australia known for its significant nickel deposits and location near Lake Lefroy.
-
D.
Chogoria
Chogoria is a town in Kenya that serves as a popular gateway and access point for climbers and trekkers heading to Mount Kenya, particularly via the Chogoria route to Point Lenana.
-
E.
Bantumi
Bantumi is a digital version of the traditional Mancala-style board game that was popularized on early Nokia mobile phones.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156d0d55c8190af59ff169e8add78 |
completed | April 16, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbc5034c8190afcaa7d35c957396 |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:53 a.m.