Triple
T22071349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hugh Downs |
E545413
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Hugh Malcolm Downs |
—
|
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: Hugh Malcolm Downs | Statement: [Hugh Downs, fullName, Hugh Malcolm Downs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hugh Malcolm Downs Context triple: [Hugh Downs, fullName, Hugh Malcolm Downs]
-
A.
Hugh Downs
chosen
Hugh Downs was a prominent American broadcaster and television host best known for his long-running roles on programs like NBC’s Today and ABC’s newsmagazine 20/20.
-
B.
Bill Cullen
Bill Cullen was a prolific American radio and television game show host best known for his quick wit and long-running presence on numerous classic quiz and panel programs.
-
C.
Hugh Bennett
Hugh Bennett was an American film editor active during Hollywood's studio era, known for his work on numerous feature films in the 1930s and 1940s.
-
D.
Jack Paar
Jack Paar was an influential American television host and comedian best known for transforming late-night TV during his tenure on The Tonight Show in the late 1950s and early 1960s.
-
E.
John Carson
John Carson is a fictional character appearing in the film "The Miracle Woman."
- 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_69e11e344dfc81909b1d88a7221329c7 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12888dcc08190b18d3d44d09ab943 |
completed | April 28, 2026, 9:37 p.m. |
Created at: April 16, 2026, 8:28 p.m.