Triple
T5695839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Can-Can |
E125536
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Cy Feuer |
E475565
|
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: Cy Feuer | Statement: [Can-Can, producer, Cy Feuer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cy Feuer Context triple: [Can-Can, producer, Cy Feuer]
-
A.
Cy Feuer
chosen
Cy Feuer was an American theater and film producer and director best known for his work on numerous successful Broadway musicals in the mid-20th century.
-
B.
Iron Felix
Iron Felix is the nickname of Felix Dzerzhinsky, the Soviet revolutionary who founded and led the Cheka, the Bolshevik secret police.
-
C.
Figan
Figan is an individual known primarily through their familial relationship as the child of Flo.
-
D.
Victor Feldbrill
Victor Feldbrill was a prominent Canadian conductor known for championing Canadian composers and leading major orchestras across the country.
-
E.
Jonathan Stark
Jonathan Stark is an American actor and television writer best known for his role in the 1985 horror-comedy film "Fright Night" and for his work on sitcoms such as "According to Jim."
- 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_69c0082bb19c8190823a4facd3cba79b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0240bde1881909f7ea13bd84deaa8 |
completed | March 22, 2026, 5:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a5635448190ada625283405752f |
completed | March 22, 2026, 9:08 p.m. |
Created at: March 22, 2026, 3:45 p.m.