Triple
T23359791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of Cameroon |
E593152
|
entity |
| Predicate | currentHolder |
P8
|
FINISHED |
| Object | Paul Biya |
—
|
NE NERFINISHED |
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: Paul Biya | Statement: [President of Cameroon, currentHolder, Paul Biya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Biya Context triple: [President of Cameroon, currentHolder, Paul Biya]
-
A.
Paul Biya
chosen
Paul Biya is the long-serving President of Cameroon, in power since 1982 and known as one of Africa’s longest-ruling leaders.
-
B.
Omar Bongo
Omar Bongo was a long-serving Gabonese politician who ruled as President of Gabon from 1967 until his death in 2009.
-
C.
Ali Bongo Ondimba
Ali Bongo Ondimba is a Gabonese politician who served as President of Gabon from 2009 until his ousting in a 2023 military coup.
-
D.
Paulin Obame-Nguema
Paulin Obame-Nguema was a Gabonese politician who served as a key government leader during the late 20th century, including a term as the country’s prime minister.
-
E.
Paul Biyoghé Mba
Paul Biyoghé Mba is a Gabonese politician who served as Prime Minister and has held several key governmental positions in Gabon.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d24d2a4819092e6ede74c2a918d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19a1a39988190b4b4993b80d5a5f6 |
completed | April 29, 2026, 5:41 a.m. |
Created at: April 17, 2026, 5:30 p.m.