Triple
T7754792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 27 Dresses |
E175864
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Roger Birnbaum |
E632592
|
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: Roger Birnbaum | Statement: [27 Dresses, producer, Roger Birnbaum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roger Birnbaum Context triple: [27 Dresses, producer, Roger Birnbaum]
-
A.
Roger Birnbaum
chosen
Roger Birnbaum is an American film producer and studio executive known for co-founding Spyglass Entertainment and producing numerous mainstream Hollywood films.
-
B.
Jerry Bresler
Jerry Bresler was an American film producer active in mid-20th-century Hollywood, known for working on large-scale studio productions.
-
C.
Michael Berman
Michael Berman is a writer and contributor known for his work published in George magazine.
-
D.
Steven Fierberg
Steven Fierberg is an American cinematographer known for his work on feature films and television series, including the romantic drama "Love & Other Drugs."
-
E.
Eric Tannenbaum
Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
- 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_69c6996180088190832e38e8d83ff54a |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c703d851d4819091e9117d3f34cb9a |
completed | March 27, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc60b0ae48190bb6e6f38bcbb05dd |
completed | April 2, 2026, 1:27 a.m. |
Created at: March 27, 2026, 4:08 p.m.