Triple
T19386971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Spy |
E484959
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Tim Bevan |
—
|
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: Tim Bevan | Statement: [London Spy, executiveProducer, Tim Bevan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tim Bevan Context triple: [London Spy, executiveProducer, Tim Bevan]
-
A.
Tim Bevan
chosen
Tim Bevan is a British film producer and co-founder of Working Title Films, known for overseeing numerous acclaimed UK and international movies.
-
B.
Eric Olthwaite
Eric Olthwaite is a comically dreary and obsessively boring Yorkshireman from the British TV comedy "Ripping Yarns," known for his fascination with shovels and rainfall statistics.
-
C.
Jim Blyth
Jim Blyth is a mountaineer known for making the first recorded ascent of Mount Carse in Antarctica.
-
D.
Michael Buckland
Michael Buckland is an American information scientist and librarian known for his influential work on information retrieval, library services, and the theory of information systems.
-
E.
Tim Fywell
Tim Fywell is a British film and television director known for his work on literary adaptations and period dramas.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b418f148190972b7b46038bc744 |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.