Triple
T14857628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dixinn |
E349399
|
entity |
| Predicate | partOfMetropolitanArea |
P294
|
FINISHED |
| Object | Greater Conakry |
E69995
|
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: Greater Conakry | Statement: [Dixinn, partOfMetropolitanArea, Greater Conakry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greater Conakry Context triple: [Dixinn, partOfMetropolitanArea, Greater Conakry]
-
A.
Conakry
chosen
Conakry is the capital and largest city of Guinea, serving as its main economic, cultural, and administrative center on the Atlantic coast of West Africa.
-
B.
Navrongo
Navrongo is a town in northern Ghana known as a key administrative and commercial center near the border with Burkina Faso.
-
C.
Korhogo
Korhogo is a major city in northern Côte d'Ivoire that serves as an important cultural and economic center for the Senufo people.
-
D.
Bamako
Bamako is the capital and largest city of Mali, serving as a major political, economic, and cultural center in West Africa.
-
E.
Serekunda
Serekunda is the most populous urban center and a major commercial hub in The Gambia.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44458ec8190be295a95f5daab14 |
completed | April 14, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef5e176081909e822881a866ecec |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 1:54 a.m.