Triple
T21855899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | December Bride |
E539624
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Verna Felton |
—
|
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: Verna Felton | Statement: [December Bride, hasCastMember, Verna Felton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verna Felton Context triple: [December Bride, hasCastMember, Verna Felton]
-
A.
Verna Felton
chosen
Verna Felton was an American character actress and voice performer best known for her memorable roles in classic Disney animated films.
-
B.
Verna Willis
Verna Willis was an American film editor and script supervisor active during Hollywood’s early studio era.
-
C.
Betty Sizemore
Betty Sizemore is the naive yet determined small-town waitress who becomes delusionally convinced she is a nurse in the dark comedy film "Nurse Betty."
-
D.
Betty McGlown
Betty McGlown was an original member of the vocal group that would later become the legendary Motown act The Supremes.
-
E.
Lurene Tuttle
Lurene Tuttle was an American character actress known for her prolific work in radio, film, and television from the 1930s through the 1970s.
- 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_69e0c47829648190bbe2d1d7033768ec |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0d635b59c81908810480f3802b847 |
completed | April 28, 2026, 3:45 p.m. |
Created at: April 16, 2026, 6:56 p.m.