Triple
T8160071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rufus Buckner |
E190553
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Rufus Buckner |
E190553
|
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 Buckner | Statement: [Rufus Buckner, name, Rufus Buckner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rufus Buckner Context triple: [Rufus Buckner, name, Rufus Buckner]
-
A.
Rufus Buckner
chosen
Rufus Buckner is an individual notable enough to be recognized as a prominent bearer of the Buckner surname.
-
B.
Manuel Buckner
Manuel Buckner is an individual notable enough to be specifically cited as a bearer of the surname Buckner.
-
C.
Robert Buckner
Robert Buckner was an American screenwriter and film producer known for his work on classic Hollywood films in the 1930s and 1940s.
-
D.
Branford Buckner
Branford Buckner is a former American football defensive tackle who played in the NFL and later became a defensive line coach.
-
E.
Hannibal Brooks
Hannibal Brooks is a 1969 British war comedy film about a prisoner of war who escapes through the Alps with an elephant, directed by Michael Winner and starring Oliver Reed.
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb45537d248190a0e998b6d336e6e1 |
completed | March 31, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd3471def08190a221e92fc4a2e9d7 |
completed | April 1, 2026, 3:06 p.m. |
Created at: March 30, 2026, 5:38 p.m.