Triple
T11008922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilda |
E260196
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Jo Eisinger |
E492423
|
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: Jo Eisinger | Statement: [Gilda, screenwriter, Jo Eisinger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jo Eisinger Context triple: [Gilda, screenwriter, Jo Eisinger]
-
A.
Jo Eisinger
chosen
Jo Eisinger was an American screenwriter best known for his dark, psychologically complex film noir scripts, including classics like "Gilda" and "Night and the City."
-
B.
Jody Gerson
Jody Gerson is a prominent American music executive and producer, best known as the CEO and Chairman of Universal Music Publishing Group.
-
C.
Robin Blaser
Robin Blaser was an American-Canadian poet, essayist, and influential figure in postwar experimental poetry associated with the San Francisco Renaissance and later the Vancouver literary scene.
-
D.
Erren Gottlieb
Erren Gottlieb is a television producer and co-creator best known for helping develop the popular educational series "Bill Nye the Science Guy."
-
E.
Jon Shestack
Jon Shestack is an American film producer known for working on a range of studio and independent movies, including the romantic comedy-drama "Dan in Real Life."
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7978810208190b8e2966ae67b6314 |
completed | April 9, 2026, 12:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3c8190c888190ba8d6fb2f4f3eb05 |
completed | April 18, 2026, 6:06 p.m. |
Created at: April 8, 2026, 9:25 p.m.