Triple
T4176585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life of Brian |
E86491
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | John Goldstone |
E357147
|
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: John Goldstone | Statement: [Life of Brian, producer, John Goldstone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Goldstone Context triple: [Life of Brian, producer, John Goldstone]
-
A.
John Goldstone
chosen
John Goldstone is a British film and television producer best known for his long association with the Monty Python comedy team.
-
B.
Paul Wattson
Paul Wattson was an American Episcopal then Catholic priest best known for his pioneering work in promoting ecumenism and Christian unity in the early 20th century.
-
C.
John Bailey
John Bailey is an American cinematographer renowned for his work on numerous acclaimed films, including the classic comedy "Groundhog Day."
-
D.
Peter Stone
Peter Stone is an American computer scientist known for his influential work in artificial intelligence and robotics, particularly in multiagent systems and robot soccer.
-
E.
Peter Stone
Peter Stone was an American screenwriter and playwright best known for crafting witty, sophisticated scripts for films such as "Charade" and the musical "1776."
- 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_69aed93de98c8190ad838ce507b77c8a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02eaa0d08190a3b805c64ef76a0c |
completed | March 9, 2026, 5:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f564c9c8190bfc321c8ec2dac14 |
completed | March 14, 2026, 3:31 p.m. |
Created at: March 9, 2026, 3:45 p.m.