Triple
T5992199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Region (Cameroon) |
E133375
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Bertoua |
E562008
|
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: Bertoua | Statement: [East Region (Cameroon), containsCity, Bertoua]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bertoua Context triple: [East Region (Cameroon), containsCity, Bertoua]
-
A.
Bertoua
chosen
Bertoua is a major city in eastern Cameroon that serves as an important administrative and commercial hub for the surrounding forested region.
-
B.
Abéché
Abéché is a major city in eastern Chad that serves as an important regional trade and administrative center.
-
C.
Maroua
Maroua is a prominent city in northern Cameroon known as a regional commercial and cultural center near the Sahel.
-
D.
Moundou
Moundou is a major city in southwestern Chad and an important industrial and commercial center, particularly known for its cotton and oil industries.
-
E.
Bangui
Bangui is the capital and largest city of the Central African Republic, serving as its political, economic, and cultural center.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04e8fd030819095a4f3b3d425ec21 |
completed | March 22, 2026, 8:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1136125808190a363a00a60d8675a |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:05 p.m.