Triple
T17056162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ndiass |
E413824
|
entity |
| Predicate | distanceToCapitalApprox |
P10889
|
FINISHED |
| Object | about 40–60 km from Dakar |
—
|
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: about 40–60 km from Dakar | Statement: [Ndiass, distanceToCapitalApprox, about 40–60 km from Dakar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCapitalApprox Context triple: [Ndiass, distanceToCapitalApprox, about 40–60 km from Dakar]
-
A.
distanceFromCapital
chosen
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
B.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
-
C.
distanceToProvinceCapital_km
Indicates the distance, measured in kilometers, between a given location and the capital city of its province.
-
D.
regionCapitalDistanceRelation
Indicates a relationship specifying the distance between a region and its capital.
-
E.
isNearCapitalCity
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db7934e881909e9f0ae956fb0816 |
completed | April 18, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.