Triple
T5916608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Mature |
E131595
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Victor John Mature |
E131595
|
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: Victor John Mature | Statement: [Victor Mature, birthName, Victor John Mature]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Victor John Mature Context triple: [Victor Mature, birthName, Victor John Mature]
-
A.
Victor Mature
chosen
Victor Mature was an American film actor known for his rugged leading-man roles in 1940s and 1950s Hollywood epics and adventure films.
-
B.
Van Johnson
Van Johnson was a popular American film and television actor of the 1940s and 1950s, known for his boy-next-door charm and roles in wartime dramas and musicals.
-
C.
Zachary Scott
Zachary Scott was an American actor best known for his suave yet often villainous roles in 1940s and 1950s Hollywood films.
-
D.
Robert Cummings
Robert Cummings was an American film and television actor best known for his roles in comedies and thrillers during Hollywood’s Golden Age.
-
E.
Stuart Erwin
Stuart Erwin was an American actor known for his work in early 20th-century film, radio, and television, often portraying affable, comedic everyman characters.
- 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_69c0085a1ed08190a7e9a8b6323fd680 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c037bcea9c8190a34dc03857e3b80b |
completed | March 22, 2026, 6:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c65fa576888190a3fd0fb3eac72a3f |
completed | March 27, 2026, 10:44 a.m. |
Created at: March 22, 2026, 3:59 p.m.