Triple
T3192218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Evans |
E66848
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Robert Evans |
E116302
|
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: Robert Evans | Statement: [Robert Evans, name, Robert Evans]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert Evans Context triple: [Robert Evans, name, Robert Evans]
-
A.
Robert Evans
chosen
Robert Evans was a prominent American film producer and studio executive who helped revive Paramount Pictures in the late 1960s and 1970s with classics like "The Godfather," "Chinatown," and "Love Story."
-
B.
Robert Evans
Robert Evans was an English estate manager best known as the father of the novelist George Eliot (Mary Ann Evans).
-
C.
Don Hahn
Don Hahn is an American film producer best known for overseeing several of Disney’s most acclaimed animated features, including Beauty and the Beast and The Lion King.
-
D.
Russell Pearce
Russell Pearce is an American politician and former Arizona state senator best known for championing hardline immigration legislation, including the controversial SB 1070 law.
-
E.
Reg Rogers
Reg Rogers is an American character actor known for his work in film, television, and theater, often portraying eccentric or villainous roles.
- 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_69ad8588ba18819086a10951c32ecb80 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6e8e4b48190bc7c6443fc6da900 |
completed | March 8, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24ba8a8b48190824dac45e37217cc |
completed | March 12, 2026, 5:14 a.m. |
Created at: March 8, 2026, 3:07 p.m.