Triple
T3056222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaches |
E60486
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Steven Poster |
E82435
|
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: Steven Poster | Statement: [Beaches, cinematographyBy, Steven Poster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steven Poster Context triple: [Beaches, cinematographyBy, Steven Poster]
-
A.
Steven Poster
chosen
Steven Poster is an American cinematographer known for his work on films such as Donnie Darko, Rocky V, and numerous other feature and television projects.
-
B.
Mark Stoermer
Mark Stoermer is an American musician best known as the longtime bassist for the rock band The Killers.
-
C.
Steven Baigelman
Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
-
D.
Philip Steuer
Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
-
E.
Sean Hartnett
Sean Hartnett is a relatively obscure individual whose primary distinguishing feature is sharing the surname Hartnett, with no widely recognized public profile or achievements documented.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf7ebd48190ad5748a18fa9a56a |
completed | March 8, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1ef0671e48190a793f907cc211dd8 |
completed | March 11, 2026, 10:39 p.m. |
Created at: March 8, 2026, 3:02 p.m.