Triple
T15010519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Etta |
E377821
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Etta Moten Barnett |
E229588
|
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: Etta Moten Barnett | Statement: [Etta, hasNotableBearer, Etta Moten Barnett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Etta Moten Barnett Context triple: [Etta, hasNotableBearer, Etta Moten Barnett]
-
A.
Etta Moten
chosen
Etta Moten was an American contralto singer and actress celebrated for breaking racial barriers on stage and screen during the 1930s and 1940s.
-
B.
Marcellite Garner
Marcellite Garner was an American voice actress best known for originating the voice of Minnie Mouse in early Disney cartoons.
-
C.
Nina Mae McKinney
Nina Mae McKinney was a pioneering African American film and stage actress and singer of the early 20th century, often hailed as one of the first Black Hollywood stars.
-
D.
Virginia Bell Horne
Virginia Bell Horne was the wife of American film and television actor Lloyd Nolan.
-
E.
Verna Fields
Verna Fields was an American film editor best known for her Oscar-winning work on the blockbuster thriller "Jaws" and her influential role in New Hollywood cinema.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded734943481908dad4ceed4fe850c |
completed | April 15, 2026, 12:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dce8240819097efddb43b79ad4b |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 2:55 a.m.