Triple
T10836540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cotton Comes to Harlem |
E255772
|
entity |
| Predicate | cinematographer |
P1953
|
FINISHED |
| Object | Gerry Hirschfeld |
E691560
|
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: Gerry Hirschfeld | Statement: [Cotton Comes to Harlem, cinematographer, Gerry Hirschfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerry Hirschfeld Context triple: [Cotton Comes to Harlem, cinematographer, Gerry Hirschfeld]
-
A.
Gerald Hirschfeld
chosen
Gerald Hirschfeld was an American cinematographer best known for his work on classic films such as Mel Brooks' comedy "Young Frankenstein."
-
B.
Guy Schuessler
Guy Schuessler is a British actor and theatre professional best known as the husband of acclaimed stage and screen actress Dame Harriet Walter.
-
C.
Paul Biegler
Paul Biegler is a small-town Michigan lawyer and the central protagonist of the courtroom drama novel and film "Anatomy of a Murder."
-
D.
Michael Wittenberg
Michael Wittenberg was an investment adviser best known as the late husband of Broadway star Bernadette Peters.
-
E.
Ira Hirschmann
Ira Hirschmann was an American businessman and diplomat best known for his World War II efforts to rescue Jews from the Holocaust and his later work in international affairs.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d746ff70148190b844ab92d796af6c |
completed | April 9, 2026, 6:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7c739708190b0d58fc2d6392c6c |
completed | April 15, 2026, 8:40 p.m. |
Created at: April 8, 2026, 9:19 p.m.