Triple
T9167047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ségou |
E219985
|
entity |
| Predicate | distanceFromBamako_km |
P84364
|
FINISHED |
| Object | approximately 235 |
—
|
LITERAL 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: approximately 235 | Statement: [Ségou, distanceFromBamako_km, approximately 235]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBamako_km Context triple: [Ségou, distanceFromBamako_km, approximately 235]
-
A.
distanceFromBamako
chosen
Indicates the spatial distance between an entity and the location of Bamako.
-
B.
distanceFromCotonou
Indicates the measured spatial distance between a given location and the city of Cotonou.
-
C.
distanceFromDakar
Indicates the spatial distance between a given entity’s location and the city of Dakar.
-
D.
distanceToLomé
Indicates the spatial distance between a given entity or location and the city of Lomé.
-
E.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
- F. None of above.
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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaade47cc81909b5c127dc8aa1340 |
completed | April 1, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69cc6605c6808190a30d92da006206ac |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:22 p.m.