Triple
T3935248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Scanlon |
E90893
|
entity |
| Predicate | name |
P16
|
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: [Dan Scanlon, name, Dan Scanlon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Scanlon Context triple: [Dan Scanlon, name, 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.
David Frankel
David Frankel is an American film and television director best known for helming popular works such as "The Devil Wears Prada" and episodes of "Sex and the City."
-
C.
James DeMonaco
James DeMonaco is an American filmmaker and screenwriter best known for creating and writing the dystopian horror franchise "The Purge."
-
D.
Dan Goor
Dan Goor is an American television writer and producer best known for co-creating the comedy series "Brooklyn Nine-Nine" and his work on shows like "Parks and Recreation."
-
E.
Brad Silberling
Brad Silberling is an American film and television director known for movies such as "City of Angels," "Casper," and "Lemony Snicket's A Series of Unfortunate Events."
- 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_69aed95f26e0819094b0e71974543a19 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeedcbf0188190a5e828707a77752a |
completed | March 9, 2026, 3:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5288b7538819084936489226dd31f |
completed | March 14, 2026, 9:21 a.m. |
Created at: March 9, 2026, 3:23 p.m.