Triple
T18375645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | central Mali |
E446306
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Ségou |
—
|
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: Ségou | Statement: [central Mali, hasCity, Ségou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ségou Context triple: [central Mali, hasCity, Ségou]
-
A.
Ségou
chosen
Ségou is a historic city in central Mali known for its role as a former Bambara kingdom capital, its Niger River location, and its rich cultural and artistic heritage.
-
B.
Koulikoro
Koulikoro is a town and region in southwestern Mali, situated along the Niger River and serving as an important administrative and transport hub.
-
C.
Mopti
Mopti is a major city in central Mali known as a bustling river port and commercial hub situated at the confluence of the Niger and Bani rivers.
-
D.
Sikasso
Sikasso is a major city in southern Mali known as an important agricultural and commercial center near the borders with Burkina Faso and Côte d'Ivoire.
-
E.
Koudougou
Koudougou is a major city in central Burkina Faso known as an important commercial and transportation hub.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51759353481908aa2de599fd2cf3b |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 10:45 a.m.