Triple
T24249261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sibut |
E603468
|
entity |
| Predicate | distanceFromBangui |
P155331
|
FINISHED |
| Object | approximately 185 km |
—
|
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 185 km | Statement: [Sibut, distanceFromBangui, approximately 185 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBangui Context triple: [Sibut, distanceFromBangui, approximately 185 km]
-
A.
distanceFromOuagadougou_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Ouagadougou.
-
B.
distanceFromBamako
Indicates the spatial distance between an entity and the location of Bamako.
-
C.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
-
D.
distanceFromJuba_km
Indicates the physical distance, measured in kilometers, between a given location and Juba.
-
E.
distanceFromBujumbura
Indicates the measured spatial distance between a given location and the city of Bujumbura.
- 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_69e29540da0481909a38bdae315b7a02 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28b87d03c8190a38ca0c0b65ce6fc |
completed | April 29, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69f1c450aa508190bc9d372a5f6ee47a |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 12:04 a.m.