Triple
T1225907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dreamgirls |
E26325
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Jamie Foxx |
E65304
|
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: Jamie Foxx | Statement: [Dreamgirls, stars, Jamie Foxx]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jamie Foxx Context triple: [Dreamgirls, stars, Jamie Foxx]
-
A.
Jamie Foxx
chosen
Jamie Foxx is an American actor, comedian, and R&B singer known for his Academy Award–winning portrayal of Ray Charles and his versatile work in film, television, and music.
-
B.
Terrence Howard
Terrence Howard is an American actor and singer known for his roles in films like "Hustle & Flow" and the TV series "Empire."
-
C.
Joseph LaShelle
Joseph LaShelle was an American cinematographer renowned for his work on numerous classic Hollywood films and for winning an Academy Award for Best Cinematography.
-
D.
Cuba Gooding Jr.
Cuba Gooding Jr. is an American actor best known for his Academy Award–winning performance in "Jerry Maguire" and prominent roles in films such as "Boyz n the Hood" and "Men of Honor."
-
E.
Will Smith
Will Smith is an American actor, rapper, and film producer known for his charismatic performances in blockbuster films and television.
- 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_69ac93bcdbbc8190a5eb1f4285faa8d4 |
completed | March 7, 2026, 9:08 p.m. |
Created at: March 1, 2026, 7:47 p.m.