Triple
T3833595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicolas Cage as Dr. Stanley Goodspeed |
E91073
|
entity |
| Predicate | writtenBy |
P806
|
FINISHED |
| Object | Mark Rosner |
E213777
|
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: Mark Rosner | Statement: [Nicolas Cage as Dr. Stanley Goodspeed, writtenBy, Mark Rosner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Rosner Context triple: [Nicolas Cage as Dr. Stanley Goodspeed, writtenBy, Mark Rosner]
-
A.
Mark Rosner
chosen
Mark Rosner is a screenwriter best known for co-writing the 1996 action film "The Rock."
-
B.
Ryan Roslansky
Ryan Roslansky is the CEO of LinkedIn, known for leading the professional networking platform’s product and business strategy.
-
C.
Marc Roskin
Marc Roskin is a television producer and director best known for his work on genre and adventure series such as "The Librarians."
-
D.
Jon Rubinstein
Jon Rubinstein is an American computer engineer and executive best known for his key role in developing Apple's iPod and later leading Palm as CEO.
-
E.
Josh Goldstein
Josh Goldstein is a screenwriter best known for co-writing the story for Disney’s adventure film "Jungle Cruise."
- 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_69aed960b538819096561c8ed448dec9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb88b8a8819082d4bdbc5bc45366 |
completed | March 9, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be395356e88190ba6c4b228669e40c |
completed | March 21, 2026, 6:23 a.m. |
Created at: March 9, 2026, 3:17 p.m.