Triple
T614932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monsters University |
E12182
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Dan Scanlon |
E90893
|
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: Dan Scanlon | Statement: [Monsters University, writer, Dan Scanlon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Scanlon Context triple: [Monsters University, writer, Dan Scanlon]
-
A.
Dan Scanlon
chosen
Dan Scanlon is an American filmmaker and animator best known for his work as a director and writer at Pixar Animation Studios.
-
B.
Paul Vogel
Paul Vogel was an American cinematographer best known for his work on classic Hollywood films, including the Oscar-winning "Battleground."
-
C.
Derek Kolstad
Derek Kolstad is an American screenwriter best known as the creator and primary writer of the John Wick action film franchise.
-
D.
Craig Zadan
Craig Zadan was an American film, television, and theater producer best known for his work on musical adaptations and live TV musicals, including projects like "Chicago" and NBC's live musical events.
-
E.
Michael Cuesta
Michael Cuesta is an American film and television director and producer known for his work on series such as Homeland, Dexter, and Six Feet Under.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e0b438881909ad515adf7a4eb79 |
completed | March 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a66d8cd1e481908b77e4db0b6681bf |
completed | March 3, 2026, 5:11 a.m. |
Created at: March 1, 2026, 7:35 p.m.