Triple
T21644349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Djenné |
E534176
|
entity |
| Predicate | Djenné-DjenoLocatedTo |
P145362
|
FINISHED |
| Object | southwest |
—
|
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: southwest | Statement: [Djenné, Djenné-DjenoLocatedTo, southwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Djenné-DjenoLocatedTo Context triple: [Djenné, Djenné-DjenoLocatedTo, southwest]
-
A.
distanceFromDakar
Indicates the spatial distance between a given entity’s location and the city of Dakar.
-
B.
primaryLocationInChad
Indicates that the referenced entity’s main or most significant location is situated within the country of Chad.
-
C.
nearestMajorTownInGuinea
Indicates that one location is the closest significant town within Guinea to another specified place.
-
D.
primaryLocationInSudan
Indicates that the primary or main location associated with an entity is situated within the country of Sudan.
-
E.
situatedNextTo
Indicates that one entity is located immediately beside another, with no significant separation between them.
- F. None of above. chosen
Provenance (4 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5393ed388190a0bc385de2b861bf |
completed | April 27, 2026, 12:16 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:35 p.m.