Triple
T22259336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rough Night |
E550176
|
entity |
| Predicate | cinematographer |
P1953
|
FINISHED |
| Object | Sean Porter |
—
|
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: Sean Porter | Statement: [Rough Night, cinematographer, Sean Porter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sean Porter Context triple: [Rough Night, cinematographer, Sean Porter]
-
A.
Sean Porter
chosen
Sean Porter is an American cinematographer known for his work on independent and genre films, including the thriller "Green Room."
-
B.
Chris Porter
Chris Porter is a music producer best known for his work on the hit song "Back for Good" by Take That.
-
C.
Chris Porter
Chris Porter is a vocalist known for providing backing vocals on notable recordings, including work associated with David Bowie's "Scary Monsters (and Super Creeps)" era.
-
D.
Eric Porter
Eric Porter was a distinguished English actor best known for his classical stage work and prominent roles in British television and film during the mid-20th century.
-
E.
Kevin Porter
Kevin Porter is an American former ice hockey center best known for his standout collegiate career at the University of Michigan and subsequent play in the NHL.
- 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c5b54c8190854690ba599639fa |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.