Triple
T4622809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CBC Film Sales Corporation |
E101025
|
entity |
| Predicate | notableExecutive |
P1918
|
FINISHED |
| Object | Joe Brandt |
E153720
|
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: Joe Brandt | Statement: [CBC Film Sales Corporation, notableExecutive, Joe Brandt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joe Brandt Context triple: [CBC Film Sales Corporation, notableExecutive, Joe Brandt]
-
A.
Joe Brandt
chosen
Joe Brandt was an American film industry executive and producer best known as one of the co-founders of Columbia Pictures.
-
B.
Doug Brandt
Doug Brandt is a film editor known for his work on major studio productions, including the adventure-comedy film "Jungle Cruise."
-
C.
Kevin Brodbin
Kevin Brodbin is a screenwriter known for his work on genre films, including the psychological thriller "Mindhunters."
-
D.
Scott Bradner
Scott Bradner is an American Internet engineer and longtime IETF leader known for his influential role in Internet standards development and governance.
-
E.
Kevin Nolting
Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
- 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_69bd43d0497c8190ac23c65c5804846a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a053d38819097b3ecbc06aa6e4d |
completed | March 20, 2026, 2:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf8575c1e48190a611bbbe9b3fb286 |
completed | March 22, 2026, 6 a.m. |
Created at: March 20, 2026, 1:12 p.m.