Triple
T8874110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sy Gomberg |
E211225
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Sy Gomberg |
E211225
|
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: Sy Gomberg | Statement: [Sy Gomberg, name, Sy Gomberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sy Gomberg Context triple: [Sy Gomberg, name, Sy Gomberg]
-
A.
Sy Gomberg
chosen
Sy Gomberg was an American screenwriter and producer known for his work in mid-20th-century Hollywood film and television and for his involvement in social and political activism.
-
B.
Ulu Grosbard
Ulu Grosbard was a Belgian-born American film and theater director known for his nuanced, character-driven dramas such as "Straight Time" and "Georgia."
-
C.
Dan Gershon
Dan Gershon is known as the brother of American actress Gina Gershon.
-
D.
Greg Grunberg
Greg Grunberg is an American actor best known for his roles in television series such as "Heroes," "Alias," and "Felicity," as well as appearances in major film franchises.
-
E.
Myron Futterman
Myron Futterman was an American businessman best known for being the first husband of actress Jane Wyman.
- 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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc614451d081908804430a72d00edf |
completed | April 1, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1c641048190aabbc10f461099f4 |
completed | April 3, 2026, 1:33 p.m. |
Created at: March 30, 2026, 6:52 p.m.