Triple
T19789422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trapped Ashes |
E475368
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object | Dick Miller |
—
|
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: Dick Miller | Statement: [Trapped Ashes, hasCastMember, Dick Miller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dick Miller Context triple: [Trapped Ashes, hasCastMember, Dick Miller]
-
A.
Dick Miller
chosen
Dick Miller was a prolific American character actor best known for his work in numerous Roger Corman films and cult classics like "Gremlins."
-
B.
JP Miller
JP Miller was an American screenwriter and playwright best known for his hard-hitting television dramas and the film adaptation of "Days of Wine and Roses."
-
C.
Ty Miller
Ty Miller is an American actor best known for his role as The Kid in the television western series "The Young Riders."
-
D.
Al Miller
Al Miller is an American soccer coach best known for his leadership roles with early North American professional teams, including the Dallas Tornado.
-
E.
Don Miller
Don Miller was a standout guard for the University of Notre Dame’s football team and one of the famed “Four Horsemen” backfield of the early 1920s.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6538ae5108190b80eb7de6f445f02 |
completed | April 20, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:49 p.m.