Triple
T2662935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lingala |
E54766
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Congo River basin |
E29137
|
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: Congo River basin | Statement: [Lingala, region, Congo River basin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Congo River basin Context triple: [Lingala, region, Congo River basin]
-
A.
Congo
Congo is a Central African country whose economy is heavily reliant on oil production and exports.
-
B.
Congo River
chosen
The Congo River is Africa’s second-longest river and the world’s deepest, flowing through central Africa to the Atlantic Ocean and serving as a major waterway for transport, ecology, and regional economies.
-
C.
Kongō
Kongō was a Japanese Kongō-class fast battleship that served prominently in the Imperial Japanese Navy during World War II.
-
D.
Athi River basin
The Athi River basin is a major drainage basin in Kenya that collects waters from rivers such as the Nairobi River and ultimately feeds into the Indian Ocean.
-
E.
Zambezi Basin
The Zambezi Basin is the vast river catchment area in southern Africa that collects the waters of the Zambezi River and its tributaries, encompassing parts of several countries and supporting major ecosystems, agriculture, and hydropower.
- 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_69abd96b9f1c8190a8a9460ca88a9aaf |
completed | March 7, 2026, 7:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf4d70388190b6f0e683c77bc262 |
completed | March 10, 2026, 5:42 a.m. |
Created at: March 6, 2026, 9:53 p.m.