Triple
T10090760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marian Marsh |
E215336
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Jean Negulesco |
E224479
|
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: Jean Negulesco | Statement: [Marian Marsh, spouse, Jean Negulesco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jean Negulesco Context triple: [Marian Marsh, spouse, Jean Negulesco]
-
A.
Jean Negulesco
chosen
Jean Negulesco was a Romanian-American film director and screenwriter best known for his stylish Hollywood dramas and romances from the 1940s and 1950s.
-
B.
Gregory La Cava
Gregory La Cava was an American film director best known for his sophisticated 1930s comedies and character-driven dramas in Hollywood’s Golden Age.
-
C.
Louis Tamburino
Louis Tamburino is a researcher known for co-authoring scholarly work with physicist Ezra Newman, likely in the field of general relativity or theoretical physics.
-
D.
Robert Tomarkin
Robert Tomarkin was the husband of Academy Award–winning American actress Dorothy Malone.
-
E.
Ivan Goff
Ivan Goff was an Australian-born screenwriter best known for his work in Hollywood film and television, including co-writing influential crime dramas and creating popular TV series.
- 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_69ca83a1eed081908b2e9580f2ebeea7 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd05960008190baecb8e4c9f2461f |
completed | April 2, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b6a587e0819093f38d5e69db43ec |
completed | April 5, 2026, 7:23 p.m. |
Created at: March 30, 2026, 9:01 p.m.