Triple
T14939443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flagler Street Bridge |
E372483
|
entity |
| Predicate | crossesInDirection |
P51219
|
FINISHED |
| Object | east–west |
—
|
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: east–west | Statement: [Flagler Street Bridge, crossesInDirection, east–west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossesInDirection Context triple: [Flagler Street Bridge, crossesInDirection, east–west]
-
A.
crossesIn
Indicates that one entity passes over or through the path, boundary, or area occupied by another entity, intersecting its space or trajectory.
-
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.
crossesTo
Indicates that one entity moves or extends from one side or area to another, passing over or through some boundary or intervening space.
-
D.
crossingDirection
chosen
Indicates the direction in which one entity moves or passes across another reference point, boundary, or path.
-
E.
crossesNear
Indicates that one entity passes across the path or area of another entity at a location that is close to, but not directly intersecting, the other entity.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded64a2f24819099b21566756668a2 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:38 a.m.