Triple
T20628890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fearless |
E506896
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Mark Rosenberg |
—
|
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: Mark Rosenberg | Statement: [Fearless, producer, Mark Rosenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Rosenberg Context triple: [Fearless, producer, Mark Rosenberg]
-
A.
Mark Rosenberg
chosen
Mark Rosenberg was an American film producer known for his work on notable movies of the 1980s and early 1990s.
-
B.
Justin Rosenberg
Justin Rosenberg is an American entrepreneur best known as the founder and CEO of the fast-casual restaurant chain Honeygrow.
-
C.
Craig Rosenberg
Craig Rosenberg is a screenwriter and producer known for his work on films and television series such as "After the Sunset" and "The Boys."
-
D.
Scott Rosenberg
Scott Rosenberg is an American screenwriter and producer known for writing high-profile films such as "Con Air," "Gone in 60 Seconds," and "High Fidelity."
-
E.
Neil Ressler
Neil Ressler is an automotive engineer and executive best known for his leadership role with Jaguar’s Formula One team in the early 2000s.
- 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe771e88190a48471bf83b4804d |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.