Triple
T26104957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gazela Bridge |
E658511
|
entity |
| Predicate | crossesInCityArea |
P54965
|
FINISHED |
| Object | central Belgrade |
—
|
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: central Belgrade | Statement: [Gazela Bridge, crossesInCityArea, central Belgrade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossesInCityArea Context triple: [Gazela Bridge, crossesInCityArea, central Belgrade]
-
A.
crossesInCity
chosen
Indicates that one entity crosses or passes through another entity within the boundaries of a specified city.
-
B.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
-
C.
crossesIn
Indicates that one entity passes over or through the path, boundary, or area occupied by another entity, intersecting its space or trajectory.
-
D.
crossesRegion
Indicates that an entity moves through or passes across the spatial extent of a specified region.
-
E.
crossesStreet
Indicates that an entity moves from one side of a street to the other, traversing the street’s width.
- 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_69ee5bc09c288190bc42a11972841383 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b3a8ae0819090189fbd8eb19f2f |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 26, 2026, 7:57 p.m.