Triple
T23209871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Bully |
E580560
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jeffrey Tambor |
—
|
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: Jeffrey Tambor | Statement: [Big Bully, starring, Jeffrey Tambor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Tambor Context triple: [Big Bully, starring, Jeffrey Tambor]
-
A.
Jeffrey Tambor
chosen
Jeffrey Tambor is an American actor known for his character roles in film and television, including acclaimed performances in series like "Arrested Development" and "Transparent."
-
B.
Don Diamont
Don Diamont is an American actor best known for his long-running roles on the soap operas "The Young and the Restless" and "The Bold and the Beautiful."
-
C.
Michel Drucker
Michel Drucker is a prominent French television host and producer known for his long-running talk and variety shows on French public and private channels.
-
D.
Alfred Margulies
Alfred Margulies is an American psychiatrist and author known for his work on the narrative and ethical dimensions of clinical practice.
-
E.
Judd Hirsch
Judd Hirsch is an American actor best known for his Emmy-winning role on the sitcom "Taxi" and his work in film, television, and theater over several decades.
- 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_69e24602ae1481908aaa6bc7ca493867 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f191609c64819096ace0d286d36f76 |
completed | April 29, 2026, 5:04 a.m. |
Created at: April 17, 2026, 4:07 p.m.