Triple
T19896059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Call Me Bwana |
E478154
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Stanley Shapiro |
—
|
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: Stanley Shapiro | Statement: [Call Me Bwana, screenwriter, Stanley Shapiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stanley Shapiro Context triple: [Call Me Bwana, screenwriter, Stanley Shapiro]
-
A.
Stanley Shapiro
chosen
Stanley Shapiro was an American screenwriter best known for his sharp comedic scripts in mid-20th-century Hollywood, including several hit romantic comedies.
-
B.
Irving Shapiro
Irving Shapiro was an influential American corporate executive and lawyer best known for leading DuPont and helping to shape modern U.S. business policy and corporate governance.
-
C.
George Shapiro
George Shapiro was a prominent American talent manager and television producer best known for managing Jerry Seinfeld and producing the hit sitcom "Seinfeld."
-
D.
Leonard Shapiro
Leonard Shapiro is a film producer best known for his work on the comedy sequel "Hamlet 2."
-
E.
Harold A. Shapiro
Harold A. Shapiro is a mathematician known for his contributions to approximation theory and numerical analysis, including coauthoring influential works with Philip J. Davis.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6593cb45881909cc34a9c601db001 |
completed | April 20, 2026, 4:50 p.m. |
Created at: April 10, 2026, 1:52 p.m.