Triple
T22546117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lorette Lue King |
E557432
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Victor Mature |
—
|
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: Victor Mature | Statement: [Lorette Lue King, spouse, Victor Mature]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Victor Mature Context triple: [Lorette Lue King, spouse, Victor 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.
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.
-
C.
Dana Andrews
Dana Andrews was a prominent American film actor of the 1940s and 1950s, best known for his leading roles in classics such as "Laura" and "The Best Years of Our Lives."
-
D.
Melvyn Douglas
Melvyn Douglas was an acclaimed American actor known for his sophisticated screen presence and award-winning performances in both classic Hollywood films and later character roles.
-
E.
Edmund Lowe
Edmund Lowe was an American film actor best known for his leading roles in silent and early sound-era Hollywood films, particularly in war dramas and comedies.
- 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f35b9888190b4e1b50d5097b211 |
completed | April 29, 2026, 1:30 a.m. |
Created at: April 16, 2026, 8:51 p.m.