Triple
T21320976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Into the Blue |
E525612
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Matt Luber |
—
|
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: Matt Luber | Statement: [Into the Blue, producer, Matt Luber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Luber Context triple: [Into the Blue, producer, Matt Luber]
-
A.
Matt Luber
chosen
Matt Luber is a film producer best known for his work on the action-thriller movie "Into the Blue."
-
B.
Matt Lammers
Matt Lammers is an individual notable enough to be specifically referenced as a bearer of the surname Lammers, though detailed public information about him is limited.
-
C.
Matt Lutsky
Matt Lutsky is a television writer and producer best known for co-creating the dark comedy series "On Becoming a God in Central Florida."
-
D.
Matt Lutz
Matt Lutz is an American actor known for his roles in film, television, and stage productions, including appearances in dramas and independent movies.
-
E.
Greg Latta
Greg Latta was an American professional football tight end who played in the World Football League and the NFL, most notably for the Chicago Bears.
- 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ed1538c8190954da114e49dfa36 |
completed | April 21, 2026, 1:42 p.m. |
Created at: April 16, 2026, 4:39 p.m.