Triple
T13438035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiwere language |
E320281
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Chiwere |
E805013
|
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: Chiwere | Statement: [Chiwere language, alternativeName, Chiwere]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chiwere Context triple: [Chiwere language, alternativeName, Chiwere]
-
A.
Chiwere
chosen
Chiwere is a Siouan language historically spoken by the Otoe-Missouria and Iowa (Ioway) Native American tribes of the central United States.
-
B.
Luchazi
Luchazi is a Bantu language spoken primarily by the Luchazi people in eastern Angola and neighboring regions.
-
C.
Bongwe
Bongwe is a dialect of the Duala language spoken by the Duala people of Cameroon.
-
D.
Chimwiini
Chimwiini is a Bantu language of the Sabaki subgroup spoken primarily along the southern Somali coast, closely related to Swahili.
-
E.
Mpongwe
Mpongwe is a Bantu language variety spoken primarily in Gabon, recognized as one of the main dialects of the Myene language cluster.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee5ec488190bd0c1e990dbd2bc2 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7547880d48190af9b30e4e521a952 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:40 p.m.