Triple
T3701841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brett Ratner |
E80794
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Brett Ratner |
E80794
|
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: Brett Ratner | Statement: [Brett Ratner, name, Brett Ratner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brett Ratner Context triple: [Brett Ratner, name, Brett Ratner]
-
A.
Brett Ratner
chosen
Brett Ratner is an American film director and producer best known for commercial hits like the Rush Hour series and X-Men: The Last Stand.
-
B.
Peter Segal
Peter Segal is an American film director known for mainstream comedies such as "Tommy Boy," "50 First Dates," and "Get Smart."
-
C.
Barry Sonnenfeld
Barry Sonnenfeld is an American filmmaker and cinematographer best known for directing the Men in Black trilogy and The Addams Family films.
-
D.
Marc Turtletaub
Marc Turtletaub is an American film producer and director known for backing acclaimed independent and character-driven movies such as "Little Miss Sunshine" and "A Beautiful Day in the Neighborhood."
-
E.
Joseph Kahn
Joseph Kahn is an American journalist who serves as the executive editor of The New York Times and is known for his leadership in global and investigative reporting.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc547c1848190a1ece46c59b7c43d |
completed | March 8, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4cdf53190819098529d11a5a3c7a8 |
completed | March 14, 2026, 2:54 a.m. |
Created at: March 8, 2026, 3:33 p.m.