Triple
T10860738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bouaké |
E256394
|
entity |
| Predicate | roadNetworkConnectsTo |
P11435
|
FINISHED |
| Object | Korhogo |
E521812
|
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: Korhogo | Statement: [Bouaké, roadNetworkConnectsTo, Korhogo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korhogo Context triple: [Bouaké, roadNetworkConnectsTo, Korhogo]
-
A.
Korhogo
chosen
Korhogo is a major city in northern Côte d'Ivoire that serves as an important cultural and economic center for the Senufo people.
-
B.
Guéckédou
Guéckédou is a town in southern Guinea known as a regional trading center near the borders with Sierra Leone and Liberia.
-
C.
Daloa
Daloa is a major inland city in western Côte d'Ivoire known as an important commercial and agricultural center, particularly for cocoa production.
-
D.
Koulikoro
Koulikoro is a town and region in southwestern Mali, situated along the Niger River and serving as an important administrative and transport hub.
-
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 (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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7515186f08190a5cc388a7d936c4f |
completed | April 9, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e373d238b88190a6f44fecfb64410c |
completed | April 18, 2026, 12:06 p.m. |
Created at: April 8, 2026, 9:20 p.m.