Triple
T2662939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lingala |
E54766
|
entity |
| Predicate | majorUrbanCenters |
P12871
|
FINISHED |
| Object | Kisangani |
E157267
|
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: Kisangani | Statement: [Lingala, majorUrbanCenters, Kisangani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kisangani Context triple: [Lingala, majorUrbanCenters, Kisangani]
-
A.
Kisangani
chosen
Kisangani is a major city in northeastern Democratic Republic of the Congo, known as a key inland port and commercial center in the central African rainforest region.
-
B.
Bangui
Bangui is the capital and largest city of the Central African Republic, serving as its political, economic, and cultural center.
-
C.
Matadi
Matadi is a major port city in western Democratic Republic of the Congo, serving as the country’s principal seaport and a key gateway for trade between the Atlantic Ocean and the interior via the Congo River.
-
D.
Kinshasa
Kinshasa is the largest city and political, economic, and cultural center of the Democratic Republic of the Congo, located along the Congo River in Central Africa.
-
E.
Lambaréné
Lambaréné is a town in western Gabon best known for its location on the Ogooué River and for hosting the historic Albert Schweitzer Hospital.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abdd1e80dc819083e04e1427d187d0 |
completed | March 7, 2026, 8:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afce812640819085c46f7452b5913b |
completed | March 10, 2026, 7:55 a.m. |
Created at: March 6, 2026, 9:53 p.m.