Triple
T19468252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramciel |
E487054
|
entity |
| Predicate | distanceFromJuba_km |
P136036
|
FINISHED |
| Object | about 250 |
—
|
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 250 | Statement: [Ramciel, distanceFromJuba_km, about 250]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromJuba_km Context triple: [Ramciel, distanceFromJuba_km, about 250]
-
A.
distanceToBujumbura_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Bujumbura.
-
B.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
-
C.
distanceFromBujumbura
Indicates the measured spatial distance between a given location and the city of Bujumbura.
-
D.
distanceFromNairobi
Indicates the spatial distance between a given entity’s location and the city of Nairobi.
-
E.
distanceFromOuagadougou_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Ouagadougou.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633e4b230819097c8804ee91988ea |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004c23308190a087b7941a90725f |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:39 p.m.