Triple
T21645475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Shore Beach |
E534201
|
entity |
| Predicate | hasViewOf |
P854
|
FINISHED |
| Object | Chicago skyline |
—
|
NE NERFINISHED |
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: Chicago skyline | Statement: [South Shore Beach, hasViewOf, Chicago skyline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chicago skyline Context triple: [South Shore Beach, hasViewOf, Chicago skyline]
-
A.
Chicago skyline
chosen
The Chicago skyline is the iconic, high-rise cityscape along Lake Michigan, renowned for its distinctive skyscrapers and architectural diversity.
-
B.
Philadelphia skyline
The Philadelphia skyline is the distinctive cluster of high-rise buildings and landmarks that defines the city’s urban silhouette along the Schuylkill and Delaware Rivers.
-
C.
Houston skyline
The Houston skyline is the distinctive cluster of high-rise buildings and skyscrapers that defines the downtown Houston cityscape.
-
D.
Detroit skyline
The Detroit skyline is the distinctive cluster of high-rise buildings and landmarks that defines the downtown and riverfront cityscape of Detroit, Michigan.
-
E.
Seattle skyline
The Seattle skyline is the iconic cityscape featuring the Space Needle and a cluster of downtown skyscrapers set against the backdrop of mountains and Puget Sound.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5394c570819081dbbe7e0f98f7d3 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 16, 2026, 6:35 p.m.