Triple
T32148347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Egermann |
E821083
|
entity |
| Predicate | nationalCinemaContextOfWork |
P55618
|
FINISHED |
| Object | Swedish cinema |
—
|
LITERAL 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: Swedish cinema | Statement: [Peter Egermann, nationalCinemaContextOfWork, Swedish cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalCinemaContextOfWork Context triple: [Peter Egermann, nationalCinemaContextOfWork, Swedish cinema]
-
A.
nationalCinema
chosen
Indicates that a film or cinematic work is associated with, produced by, or representative of a particular nation’s cinema.
-
B.
filmStudioCountry
Indicates the country in which a film studio is based or primarily operates.
-
C.
productionCountryOfWorkAppearsIn
Indicates that a country is the production country of a work in which a given entity appears.
-
D.
cinemaOf
Indicates a relationship where a cinema is associated with, belongs to, or is located within a particular place, organization, or context.
-
E.
filmCountryOfOrigin
Indicates the country where a film was originally produced or created.
- F. None of above.
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_69f3490520d081909b2f1271dab75faa |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 1, 2026, 12:31 a.m.