Triple
T34277961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wusi Dajie |
E879514
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | road in Beijing |
C36278
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: road in Beijing Context triple: [Wusi Dajie, instanceOf, road in Beijing]
-
A.
street in Beijing
chosen
A street in Beijing is a public urban thoroughfare lined with a mix of traditional and modern buildings, bustling with pedestrians, cyclists, and vehicles, and often featuring shops, food stalls, and cultural landmarks.
-
B.
road in Shanghai
A road in Shanghai is a transportation corridor within the city’s dense urban fabric that supports mixed traffic—vehicles, buses, bicycles, and pedestrians—while integrating local infrastructure, commercial activity, and municipal regulations specific to Shanghai.
-
C.
road in Shenzhen
A road in Shenzhen is a transportation corridor within the city’s dense, rapidly developed urban fabric, designed to support high volumes of vehicular, public transit, and pedestrian traffic while integrating with modern infrastructure and smart-city systems.
-
D.
road in Berlin
A road in Berlin is a public thoroughfare within the city’s urban network that facilitates vehicular, bicycle, and pedestrian movement while integrating with Berlin’s historical layout, public transit, and zoning infrastructure.
-
E.
road in Moscow
A road in Moscow is a transportation route within the city’s urban network that facilitates vehicular and pedestrian movement between various districts, landmarks, and infrastructure.
- F. None of above.
Provenance (1 batch)
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_69f349b5f6648190b9420d94a4cd16e0 |
completed | April 30, 2026, 12:23 p.m. |
Created at: May 1, 2026, 1:57 a.m.