Triple
T618910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazzaville |
E14466
|
entity |
| Predicate | distanceToKinshasa |
P16704
|
FINISHED |
| Object | about 1–2 km across the river |
—
|
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 1–2 km across the river | Statement: [Brazzaville, distanceToKinshasa, about 1–2 km across the river]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToKinshasa Context triple: [Brazzaville, distanceToKinshasa, about 1–2 km across the river]
-
A.
distanceToHarare
Indicates the spatial distance between a given entity and the location of Harare.
-
B.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
-
C.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
D.
distanceToSouthAfrica
Indicates the measured or calculated spatial distance between a given entity and the country of South Africa.
-
E.
distanceToContinentApproximate
Indicates an approximate measure of how far something is from a specified continent.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e25956c8190a1eed87002548658 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfd15288190b4abdbd0bce3edcd |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49d76062c819083ac33f1f87097c7 |
completed | March 1, 2026, 8:11 p.m. |
Created at: March 1, 2026, 7:35 p.m.