Triple
T4170845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rising Star Award |
E84557
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object | John Boyega |
E11429
|
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: John Boyega | Statement: [Rising Star Award, notableRecipient, John Boyega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Boyega Context triple: [Rising Star Award, notableRecipient, John Boyega]
-
A.
John Boyega
chosen
John Boyega is a British actor and producer best known for his role as Finn in the Star Wars sequel trilogy.
-
B.
Daisy Ridley
Daisy Ridley is an English actress best known for portraying Rey in the Star Wars sequel trilogy and for roles in films such as Murder on the Orient Express (2017).
-
C.
Naomi Scott
Naomi Scott is a British actress and singer best known for playing Princess Jasmine in Disney’s live-action Aladdin and performing its signature song “A Whole New World.”
-
D.
Tye Sheridan
Tye Sheridan is an American actor known for roles in films such as Mud, Ready Player One, and the X-Men series, where he portrays the young Cyclops.
-
E.
Alan Tudyk
Alan Tudyk is an American actor and voice actor known for his versatile character roles in films, television, and animation, including work with Disney and on series like "Firefly."
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c87cc88190a9ec3712db18a8a7 |
completed | March 9, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f4ef1a08190a232ed94595a86e8 |
completed | March 14, 2026, 3:31 p.m. |
Created at: March 9, 2026, 3:45 p.m.