Triple
T20808490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twin Beds |
E512231
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | William Yetter Sr. |
—
|
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: William Yetter Sr. | Statement: [Twin Beds, hasCastMember, William Yetter Sr.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Yetter Sr. Context triple: [Twin Beds, hasCastMember, William Yetter Sr.]
-
A.
William Yetter Sr.
chosen
William Yetter Sr. was an American film actor known for his supporting and bit roles in early 20th-century Hollywood cinema.
-
B.
William Wheeler
William Wheeler is an American screenwriter known for his work on films such as the biographical drama "Queen of Katwe."
-
C.
William Lochren
William Lochren was a 19th-century American jurist who served as a United States federal judge.
-
D.
George Shively
George Shively was an early 20th-century Negro league outfielder known for his speed, strong defense, and key role on several prominent Black baseball teams.
-
E.
William Boyett
William Boyett was an American character actor best known for his numerous television roles, particularly as law enforcement figures in series like "Adam-12" and "Dragnet."
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2d0a2a081908fb0e3d890e87aaf |
completed | April 21, 2026, 12:20 a.m. |
Created at: April 16, 2026, 12:40 p.m.