Triple
T5974669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sid Silvers |
E132955
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sid Silvers |
E132955
|
NE FINISHED |
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: Sid Silvers | Statement: [Sid Silvers, name, Sid Silvers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sid Silvers Context triple: [Sid Silvers, name, Sid Silvers]
-
A.
Sid Silvers
chosen
Sid Silvers was an American comedian, actor, and writer known for his work in early Hollywood musicals and comedies.
-
B.
Winston Silver
Winston Silver is a lighter, lower-tar and nicotine variant of the Winston brand of cigarettes.
-
C.
Mace Siegel
Mace Siegel was an American real estate developer and businessman best known as a co-founder and longtime leader of The Macerich Company, one of the largest shopping center owners in the United States.
-
D.
Louis Silvers
Louis Silvers was an American composer and musical director best known for scoring early sound films in Hollywood during the late 1920s and 1930s.
-
E.
Phil Silvers
Phil Silvers was an American comedian and actor best known for his fast-talking, scheming persona, especially in the classic TV series "The Phil Silvers Show" where he played Sergeant Bilko.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a39c9d08190a78e1e3268584eb5 |
completed | March 22, 2026, 7:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e41459c88190a9e0ee0321946e57 |
completed | March 23, 2026, 6:56 a.m. |
Created at: March 22, 2026, 4:03 p.m.