Triple
T618923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazzaville |
E14466
|
entity |
| Predicate | isAcrossFrom |
P382
|
FINISHED |
| Object | Kinshasa, capital of the Democratic Republic of the Congo |
—
|
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: Kinshasa, capital of the Democratic Republic of the Congo | Statement: [Brazzaville, isAcrossFrom, Kinshasa, capital of the Democratic Republic of the Congo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAcrossFrom Context triple: [Brazzaville, isAcrossFrom, Kinshasa, capital of the Democratic Republic of the Congo]
-
A.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
B.
builtAcrossStreetFrom
Indicates that one structure was constructed on the opposite side of a street directly facing another structure.
-
C.
locatedAtIntersectionOf
Indicates that something is situated at the point where two or more paths, roads, or boundaries cross or meet.
-
D.
locatedAcrossRiverFrom
chosen
Indicates that one entity is situated on the opposite side of a river relative to another entity.
-
E.
hasNearbyStreet
Indicates that one entity is located close to or adjacent to a street.
- 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_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. |
Created at: March 1, 2026, 7:35 p.m.