Triple
T1225853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Precious |
E26324
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Gabourey Sidibe |
E140727
|
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: Gabourey Sidibe | Statement: [Precious, castMember, Gabourey Sidibe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabourey Sidibe Context triple: [Precious, castMember, Gabourey Sidibe]
-
A.
Gabourey Sidibe
chosen
Gabourey Sidibe is an American actress best known for her acclaimed, Oscar-nominated breakout performance in the film "Precious."
-
B.
Octavia Spencer
Octavia Spencer is an American actress and producer acclaimed for her powerful character roles in film and television, including her Oscar-winning performance in "The Help."
-
C.
Gabrielle Union
Gabrielle Union is an American actress, author, and producer known for her roles in films like "Bring It On" and "Bad Boys II" as well as the TV series "Being Mary Jane."
-
D.
Angela Bassett
Angela Bassett is an acclaimed American actress known for her powerful performances in film and television, particularly in biographical and dramatic roles.
-
E.
Lupita Nyong'o
Lupita Nyong'o is a Kenyan-Mexican actress acclaimed for her powerful film performances, stage work, and advocacy for diversity and representation in Hollywood.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be39908481908cca21aaf0828415 |
completed | March 1, 2026, 10:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8f71aaa481909736d21705744341 |
completed | March 7, 2026, 8:49 p.m. |
Created at: March 1, 2026, 7:47 p.m.