Triple
T4330528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aladdin (2019 film) |
E96736
|
entity |
| Predicate | castMember |
P1668
|
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: [Aladdin (2019 film), castMember, Will Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Will Smith Context triple: [Aladdin (2019 film), castMember, 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.
Martin Lawrence
Martin Lawrence is an American comedian and actor best known for his energetic stand-up, his hit sitcom "Martin," and his leading roles in the "Bad Boys" film series alongside Will Smith.
-
C.
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."
-
D.
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.
-
E.
Terrence Howard
Terrence Howard is an American actor and singer known for his roles in films like "Hustle & Flow" and the TV series "Empire."
- 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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3514c39748190900e13e70ed8848c |
completed | March 12, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d09fad588190b488012b4fc6cb8c |
completed | March 14, 2026, 9:18 p.m. |
Created at: March 12, 2026, 11:13 p.m.