Triple
T20029299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forky Asks a Question |
E495078
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Mark Nielsen |
—
|
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 Nielsen | Statement: [Forky Asks a Question, producer, Mark Nielsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Nielsen Context triple: [Forky Asks a Question, producer, Mark Nielsen]
-
A.
Mark Nielsen
chosen
Mark Nielsen is a film producer best known for his work on Pixar's animated feature "Toy Story 4."
-
B.
Victor Kilian
Victor Kilian was an American character actor known for his prolific work in film and television from the 1920s through the 1970s.
-
C.
Jesse James Garrett
Jesse James Garrett is an American user experience designer and author best known for coining the term AJAX and influencing modern web application design.
-
D.
Bill Buxton
Bill Buxton is a pioneering computer scientist and designer known for his influential work in human-computer interaction, input technologies, and user experience design.
-
E.
Tim Ives
Tim Ives is an American cinematographer known for his work on acclaimed film and television projects, including series like "Stranger Things" and "Girls."
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662908df081909a6c8ccf0dd90fff |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:36 p.m.