Triple
T8094984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montmorency plateau |
E188959
|
entity |
| Predicate | hasViewOf |
P854
|
FINISHED |
| Object | Paris skyline |
E251804
|
NE 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: Paris skyline | Statement: [Montmorency plateau, hasViewOf, Paris skyline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paris skyline Context triple: [Montmorency plateau, hasViewOf, Paris skyline]
-
A.
Paris skyline
chosen
The Paris skyline is the iconic cityscape of France’s capital, marked by landmarks like the Eiffel Tower, historic Haussmannian rooftops, and church spires rising above the urban landscape.
-
B.
Manhattan skyline
The Manhattan skyline is the iconic, densely packed silhouette of New York City’s skyscrapers, prominently featuring landmarks like One World Trade Center and the Empire State Building.
-
C.
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.
-
D.
Paris Bar
The Paris Bar is the professional association and regulatory body for lawyers practicing in Paris, France.
-
E.
Chicago skyline
The Chicago skyline is the iconic, high-rise cityscape along Lake Michigan, renowned for its distinctive skyscrapers and architectural diversity.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb429089cc81909e4625f9cc7e305f |
completed | March 31, 2026, 3:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc6414ca048190ac0e644b2c399bfb |
completed | April 1, 2026, 12:17 a.m. |
Created at: March 30, 2026, 5:30 p.m.