Triple
T20154317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Free Cinema |
E491513
|
entity |
| Predicate | keyFigure |
P256
|
FINISHED |
| Object | Gavin Lambert |
—
|
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: Gavin Lambert | Statement: [Free Cinema, keyFigure, Gavin Lambert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gavin Lambert Context triple: [Free Cinema, keyFigure, Gavin Lambert]
-
A.
Gavin Lambert
chosen
Gavin Lambert was a British-born screenwriter, novelist, and film critic known for his incisive Hollywood stories and adaptations, including several acclaimed mid-20th-century films.
-
B.
Gavin Thorpe
Gavin Thorpe is a British author and game designer best known for his novels and work on the Warhammer and Warhammer 40,000 universes for Games Workshop and Black Library.
-
C.
Andrew Lambert
Andrew Lambert is a British naval historian and academic known for his work on maritime history and strategy.
-
D.
Jonathan Gledhill
Jonathan Gledhill was an English Anglican bishop who served in senior episcopal roles in the Church of England, including as Bishop of Stafford.
-
E.
Gavin Hughes
Gavin Hughes is a character in J.K. Rowling’s contemporary novel *The Casual Vacancy*, involved in the small-town political and social tensions that drive the story.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667de9bec8190836887c86dbcf28d |
completed | April 20, 2026, 5:52 p.m. |
Created at: April 11, 2026, 11:34 p.m.