Triple
T9416028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ubangi River |
E227021
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Bangui |
E148403
|
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: Bangui | Statement: [Ubangi River, passesNear, Bangui]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bangui Context triple: [Ubangi River, passesNear, Bangui]
-
A.
Bangui
chosen
Bangui is the capital and largest city of the Central African Republic, serving as its political, economic, and cultural center.
-
B.
Abéché
Abéché is a major city in eastern Chad that serves as an important regional trade and administrative center.
-
C.
Moundou
Moundou is a major city in southwestern Chad and an important industrial and commercial center, particularly known for its cotton and oil industries.
-
D.
Bamenda
Bamenda is a prominent city in northwestern Cameroon known as a cultural and commercial hub of the Anglophone region.
-
E.
Ouaga
Ouaga is the commonly used short name for Ouagadougou, the capital and largest city of Burkina Faso.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68c9917481909f793a2a9efb2a75 |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12233f89c8190979d76aee65c0d56 |
completed | April 4, 2026, 2:37 p.m. |
Created at: March 30, 2026, 7:48 p.m.