Triple
T22639975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The World of Jeeves |
E558795
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Bertram Wooster |
—
|
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: Bertram Wooster | Statement: [The World of Jeeves, mainCharacter, Bertram Wooster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bertram Wooster Context triple: [The World of Jeeves, mainCharacter, Bertram Wooster]
-
A.
Bertie Wooster
chosen
Bertie Wooster is a wealthy, amiable, and somewhat dim-witted young English gentleman best known as the hapless master of the supremely competent valet Jeeves in P. G. Wodehouse’s comic stories.
-
B.
Tim Wooster
Tim Wooster is a cinematographer known for his work on the film "Exam."
-
C.
Jeeves
Jeeves is the famously unflappable and supremely competent valet who serves as the central comic foil and problem-solver in P. G. Wodehouse’s stories about Bertie Wooster.
-
D.
Terry Jeeves
Terry Jeeves was a British science fiction fan and fanzine artist known for his influential contributions to fandom and his award-winning fan artwork.
-
E.
Charlie Wooster
Charlie Wooster is the comic, good-natured cook on the classic American Western television series "Wagon Train."
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17010aa4c8190a9f0cf7eb4c066cd |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:04 p.m.