Triple
T15311538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boy (2016 film) |
E366049
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Brian Berdan |
E323818
|
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: Brian Berdan | Statement: [The Boy (2016 film), editedBy, Brian Berdan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brian Berdan Context triple: [The Boy (2016 film), editedBy, Brian Berdan]
-
A.
Brian Berdan
chosen
Brian Berdan is a film editor known for his work on action-packed movies such as "Crank: High Voltage."
-
B.
Daniel Krumitz
Daniel Krumitz is a brilliant but socially awkward FBI cyber forensics expert featured as a central character in the television series CSI: Cyber.
-
C.
Charles Heerey
Charles Heerey was a Catholic prelate and missionary bishop who played a significant role in the hierarchy of the Church in Nigeria.
-
D.
Wilson Benge
Wilson Benge was a British character actor, often cast as butlers or servants, who appeared in numerous Hollywood films during the early 20th century.
-
E.
Charles Horvath
Charles Horvath was an American actor and stuntman known for his rugged roles in Westerns and action films.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03cd2d5a88190aead748920f93d47 |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8a20c1881909b387aed6f532c3d |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:16 a.m.