Triple
T23149215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ewondo language |
E578275
|
entity |
| Predicate | hasEndonym |
P1435
|
FINISHED |
| Object | Ewondo |
E138978
|
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: Ewondo | Statement: [Ewondo language, hasEndonym, Ewondo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ewondo Context triple: [Ewondo language, hasEndonym, Ewondo]
-
A.
Ewondo
chosen
Ewondo is a Bantu language spoken primarily by the Ewondo people in central Cameroon, including in and around the capital city, Yaoundé.
-
B.
Benina
Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
-
C.
N’Guigmi
N’Guigmi is a town and commune in southeastern Niger, located near Lake Chad and serving as an important local center for trade and transport.
-
D.
Ebanga
Ebanga is a monoclonal antibody drug used to treat Zaire ebolavirus infection (Ebola virus disease).
-
E.
Wele-Nzas
Wele-Nzas is a province in mainland Equatorial Guinea known for its forests, border location near Gabon and Cameroon, and the city of Mongomo.
- 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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18ed0b76c8190ac61b949d88e9970 |
completed | April 29, 2026, 4:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c30963b3c8190a4ffb48b03fbf77a |
completed | May 19, 2026, 9:42 a.m. |
Created at: April 17, 2026, 4:01 p.m.