Triple
T8250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklyn Bridge |
E163
|
entity |
| Predicate | trafficType |
P621
|
FINISHED |
| Object | motor vehicles |
—
|
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: motor vehicles | Statement: [Brooklyn Bridge, trafficType, motor vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trafficType Context triple: [Brooklyn Bridge, trafficType, motor vehicles]
-
A.
transportation
Indicates the movement of someone or something from one place to another, typically using a vehicle or transit system.
-
B.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
C.
visitorCount
Indicates the number of visitors associated with a particular entity, context, or time period.
-
D.
mediaType
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
E.
trackGauge
Indicates the distance between the inner faces of the rails in a railway track system.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2407916ac8190b76d2e6690efaef3 |
completed | Feb. 28, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69a23fe3a87881909ab95bb3a0b474ec |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a240782e108190b6b60c26b84ae179 |
completed | Feb. 28, 2026, 1:10 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.