Triple
T18336414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ken Waller |
E439282
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ken Waller |
—
|
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: Ken Waller | Statement: [Ken Waller, name, Ken Waller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Waller Context triple: [Ken Waller, name, Ken Waller]
-
A.
Ken Waller
chosen
Ken Waller is an American bodybuilder best known for his appearances in the 1970s bodybuilding scene and his prominent role in the documentary film "Pumping Iron."
-
B.
Clinton Winkler
Clinton Winkler was a 19th-century Texas judge and politician for whom Winkler County in Texas is named.
-
C.
Connell Waldron
Connell Waldron is a sensitive, working-class Irish teenager whose complex relationship with Marianne Sheridan forms the emotional core of Sally Rooney’s novel and its television adaptation, "Normal People."
-
D.
Phil Morrow
Phil Morrow is a television producer known for his work in developing and producing various entertainment and factual programs.
-
E.
Walt Garrison
Walt Garrison was an American football fullback for the Dallas Cowboys and a celebrated rodeo cowboy known for his toughness and dual-sport career.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ecd759481909703ed2d0d68199f |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:37 a.m.