Triple
T15276241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Buckley |
E365147
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | James Buckley |
E365147
|
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: James Buckley | Statement: [James Buckley, name, James Buckley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Buckley Context triple: [James Buckley, name, James Buckley]
-
A.
James Buckley
chosen
James Buckley is an English actor and comedian best known for playing Jay Cartwright in the British sitcom "The Inbetweeners."
-
B.
Thomas Buckley
Thomas Buckley is a personal name shared by multiple individuals, including various notable figures in fields such as politics, sports, and the arts.
-
C.
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.
-
D.
Patrick Buckley
Patrick Buckley is a personal name shared by multiple individuals, including various professionals and public figures across fields such as politics, sports, and business.
-
E.
Michael Buckley
Michael Buckley is a common name shared by several notable individuals, including authors, entertainers, and public figures across different fields.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00952731c8190bf6a5e6e10c95b94 |
completed | April 15, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01e092408190aec1561e78ea0acb |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:14 a.m.