Triple
T6205598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Cruise |
E138735
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Mimi Rogers |
E474135
|
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: Mimi Rogers | Statement: [Tom Cruise, spouse, Mimi Rogers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mimi Rogers Context triple: [Tom Cruise, spouse, Mimi Rogers]
-
A.
Mimi Rogers
chosen
Mimi Rogers is an American actress and former model known for her work in film and television since the 1980s, including notable roles in movies like "The Rapture" and "Austin Powers: International Man of Mystery."
-
B.
Mimi Thompson
Mimi Thompson is the wife of American pop artist James Rosenquist.
-
C.
Lisa Gottsegen
Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
-
D.
Tamara Miller
Tamara Miller is a member of the Disney family and a granddaughter of Walt Disney through his daughter Diane Disney Miller.
-
E.
Mimi O’Malley Baker
Mimi O’Malley Baker is best known as the wife of Pulitzer Prize–winning American journalist and humorist Russell Baker.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626f85748190a94448117a85fd78 |
completed | March 22, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cb9f421081908b9df22decae8923 |
completed | March 28, 2026, 12:37 p.m. |
Created at: March 22, 2026, 4:20 p.m.