Triple
T4197964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Boys for Life |
E85998
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Will Smith |
E140767
|
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: Will Smith | Statement: [Bad Boys for Life, producer, Will Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Will Smith Context triple: [Bad Boys for Life, producer, Will Smith]
-
A.
Will Smith
chosen
Will Smith is an American actor, rapper, and film producer known for his charismatic performances in blockbuster films and television.
-
B.
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."
-
C.
Hill Harper
Hill Harper is an American actor and author best known for his role as Dr. Sheldon Hawkes on the television series CSI: NY.
-
D.
Terrence Howard
Terrence Howard is an American actor and singer known for his roles in films like "Hustle & Flow" and the TV series "Empire."
-
E.
Jamie Foxx
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.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0360bc8081908ceb2483eef89174 |
completed | March 9, 2026, 5:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b58a12c11481908033229ecf90c9f9 |
completed | March 14, 2026, 4:17 p.m. |
Created at: March 9, 2026, 3:48 p.m.