Triple
T20915570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wally Cassell |
E515062
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Wally Cassell |
—
|
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: Wally Cassell | Statement: [Wally Cassell, name, Wally Cassell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wally Cassell Context triple: [Wally Cassell, name, Wally Cassell]
-
A.
Wally Cassell
chosen
Wally Cassell was an Italian-born American character actor known for his supporting roles in numerous Hollywood films of the 1940s and 1950s.
-
B.
Wally Dalton
Wally Dalton is an actor known for his role in the independent drama film "Wendy and Lucy."
-
C.
Wally Wilkinson
Wally Wilkinson is a musician best known as an early member of the New Zealand art rock band Split Enz.
-
D.
Wallace Wood
Wallace Wood was an influential American comic book artist and writer, best known for his work with EC Comics, Mad magazine, and early Marvel titles.
-
E.
Wally Pinner
Wally Pinner is the central character of the British film "The Punch and Judy Man," a seaside puppeteer whose struggles reflect themes of class, tradition, and small-town life.
- 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec628a38819093dcb70de91c770b |
completed | April 21, 2026, 3:17 a.m. |
Created at: April 16, 2026, 12:48 p.m.