Triple
T21366192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kennedy Bridge |
E526920
|
entity |
| Predicate | crossesAt |
P10257
|
FINISHED |
| Object | Niamey |
—
|
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: Niamey | Statement: [Kennedy Bridge, crossesAt, Niamey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niamey Context triple: [Kennedy Bridge, crossesAt, Niamey]
-
A.
Niamey
chosen
Niamey is the capital and largest city of Niger, situated along the Niger River and serving as the country’s political, economic, and cultural center.
-
B.
Niamey Zarma
Niamey Zarma is the principal urban dialect of the Zarma language, predominantly spoken in and around Niger’s capital city, Niamey.
-
C.
Bamako
Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
-
D.
Yamoussoukro
Yamoussoukro is the political capital of Côte d'Ivoire, known for its grand basilica and role as an administrative center in the French-speaking world.
-
E.
Ouagadougou
Ouagadougou is the capital and largest city of Burkina Faso, serving as its political, economic, and cultural center in the Sahel region.
- 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b06fbe108190a07a46824b96a963 |
completed | April 22, 2026, 11:26 a.m. |
Created at: April 16, 2026, 5:09 p.m.