Triple
T18208083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Truth or Consequences |
E435957
|
entity |
| Predicate | host |
P2592
|
FINISHED |
| Object | Steve Dunne |
—
|
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: Steve Dunne | Statement: [Truth or Consequences, host, Steve Dunne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Dunne Context triple: [Truth or Consequences, host, Steve Dunne]
-
A.
Steve Dunne
chosen
Steve Dunne was an American actor and radio personality best known for his work in mid-20th-century film, television, and radio drama.
-
B.
Philip Dunn
Philip Dunn is a relatively obscure individual whose specific public notability is not clearly established from the available information.
-
C.
John Harrold
John Harrold is a British illustrator best known for his long-running work on the Rupert Bear comic strips and annuals.
-
D.
Ian Dunn
Ian Dunn is a British actor known for his work in television, film, and theatre, and for being married to the late actress Emma Chambers.
-
E.
Arthur Dunn
Arthur Dunn was an English educator and former footballer best known for establishing the prestigious preparatory institution Ludgrove School.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e2261a848190b62a8485009f8f38 |
completed | April 19, 2026, 2:09 p.m. |
Created at: April 10, 2026, 10:32 a.m.