Triple
T22103911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Education (2019 film) |
E546236
|
entity |
| Predicate | setIn |
P1393
|
FINISHED |
| Object | Roslyn, New York |
—
|
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: Roslyn, New York | Statement: [Bad Education (2019 film), setIn, Roslyn, New York]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roslyn, New York Context triple: [Bad Education (2019 film), setIn, Roslyn, New York]
-
A.
Roslyn
chosen
Roslyn is a historic, affluent village in Nassau County, New York, known for its picturesque harbor, preserved 18th- and 19th-century architecture, and role as a prominent residential community on Long Island’s North Shore.
-
B.
Roslyn
Roslyn is a residential suburb located within the city of Palmerston North in New Zealand.
-
C.
Roslyn
Roslyn is a .NET compiler platform and set of open-source APIs developed by Microsoft that provides rich code analysis, refactoring, and compilation services for C# and Visual Basic.
-
D.
Clinton, New York
Clinton, New York is a small village in Oneida County known for its historic charm and as the home of Hamilton College.
-
E.
Rochester, New York
Rochester, New York is a major city in western New York State known for its industrial history, universities, and cultural institutions along the Genesee River.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1291815f88190a6eaf73e444dc1c2 |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.