Triple
T7499457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Time to Kill |
E177220
|
entity |
| Predicate | characterPortrayed |
P1507
|
FINISHED |
| Object | Rufus Buckley |
E690906
|
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: Rufus Buckley | Statement: [A Time to Kill, characterPortrayed, Rufus Buckley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rufus Buckley Context triple: [A Time to Kill, characterPortrayed, Rufus Buckley]
-
A.
Rufus Buckley
chosen
Rufus Buckley is an ambitious and politically driven prosecutor in John Grisham’s legal thriller "A Time to Kill."
-
B.
Richard Buckley
Richard Buckley was an American fashion journalist and editor, best known for his long career at magazines like Vogue and Vanity Fair and his decades-long partnership with designer Tom Ford.
-
C.
Stephen Burbank
Stephen Burbank is a prominent legal scholar and professor known for his expertise in civil procedure and complex litigation at the University of Pennsylvania Law School.
-
D.
Rob Buckley
Rob Buckley is a relatively obscure individual whose name is notably associated with the surname Buckley but who has no widely recognized public profile.
-
E.
Paul Buckley
Paul Buckley is a name shared by several notable individuals, including professionals in fields such as sports, academia, and the arts.
- 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_69c69f2696688190915a8458f2398211 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f598dfac8190a123daaac0784aee |
completed | March 27, 2026, 9:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c963e3a3e0819092c6c7dd0dc82e7d |
completed | March 29, 2026, 5:39 p.m. |
Created at: March 27, 2026, 3:44 p.m.