Triple
T18968193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clockwise |
E464096
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Peter Tanner |
—
|
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: Peter Tanner | Statement: [Clockwise, editor, Peter Tanner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Tanner Context triple: [Clockwise, editor, Peter Tanner]
-
A.
Peter Tanner
chosen
Peter Tanner was a British film editor known for his work on numerous feature films, including the Vietnam War drama "Hamburger Hill."
-
B.
Jack Tanner
Jack Tanner is the radical, free-thinking protagonist of George Bernard Shaw's play "Man and Superman," known for his iconoclastic views on politics, marriage, and social conventions.
-
C.
Peter Scudder
Peter Scudder is a fictional character, most notably appearing as a key figure in John le Carré’s spy novel "The Little Drummer Girl."
-
D.
Peter Turner
Peter Turner is a British actor and writer best known for his memoir about his relationship with Gloria Grahame, which was adapted into the film "Film Stars Don’t Die in Liverpool."
-
E.
David Tanner
David Tanner is a film and television producer best known for his work on the British drama series "Red, White and Blue."
- 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_69d8dcffc278819086792a4ebfddfafa |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6172888819090a8b3cb1db20496 |
completed | April 20, 2026, 7:30 a.m. |
Created at: April 10, 2026, noon