Triple
T21341259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel Spewack |
E526196
|
entity |
| Predicate | coAuthor |
P398
|
FINISHED |
| Object | Bella Spewack |
E502661
|
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: Bella Spewack | Statement: [Samuel Spewack, coAuthor, Bella Spewack]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bella Spewack Context triple: [Samuel Spewack, coAuthor, Bella Spewack]
-
A.
Bella Spewack
chosen
Bella Spewack was an American playwright, screenwriter, and librettist best known for her collaborations with her husband Samuel Spewack on works such as the musical "Kiss Me, Kate."
-
B.
Tillie Siegel
Tillie Siegel is a fictional character appearing in the film "A Family Affair."
-
C.
Wanda Tuchock
Wanda Tuchock was an American screenwriter and film director active during Hollywood’s early sound era, known as one of the few women writing and directing studio features in the 1930s.
-
D.
Sara Kestelman
Sara Kestelman is a British actress known for her work in film, television, and theatre, including a notable role in the 1974 science fiction film "Zardoz."
-
E.
Lisa Fruchtman
Lisa Fruchtman is an American film editor known for her work on major films such as "Apocalypse Now" and for winning an Academy Award for Best Film Editing.
- 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_69e0b51c33048190ab27cede74ef798c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5ba7ce3c8190ba5ded980a9866f2 |
completed | April 26, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09ad58a7488190bf8478966cb4eb16 |
completed | May 17, 2026, 11:58 a.m. |
Created at: April 16, 2026, 4:44 p.m.