Triple
T29728059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tour Avant-Seine |
E752237
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | skyscraper in Paris |
C6907
|
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: skyscraper in Paris Context triple: [Tour Avant-Seine, instanceOf, skyscraper in Paris]
-
A.
skyscraper in Montreal
A skyscraper in Montreal is a tall, multi-story commercial or residential building that shapes the city's skyline while reflecting its blend of modern architecture and North American–European cultural influences.
-
B.
skyscraper in Berlin
A skyscraper in Berlin is a tall, multi-story commercial or mixed-use building that rises prominently above the city’s predominantly mid-rise skyline, integrating modern architecture with the urban fabric and historical context of the German capital.
-
C.
landmark in Paris
chosen
A landmark in Paris is a notable and often historic site, structure, or monument within the city that serves as a recognizable symbol of its cultural, architectural, or social identity.
-
D.
skyscraper in Hong Kong
A skyscraper in Hong Kong is a tall, high-density commercial or residential building that contributes to the city’s iconic vertical skyline, often integrating mixed-use spaces and advanced structural engineering to maximize limited urban land.
-
E.
skyscraper in Seattle
A skyscraper in Seattle is a tall, multi-story commercial or mixed-use building that defines the city's skyline, often featuring modern architecture, glass facades, and views of Puget Sound and the surrounding mountains.
- 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_69f0d62a36a88190bf860f00da433ff8 |
completed | April 28, 2026, 3:45 p.m. |
Created at: April 28, 2026, 7:40 p.m.