Triple
T20575695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Dust |
E505211
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Tom Hooper |
—
|
NE NERFINISHED |
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: Tom Hooper | Statement: [Red Dust, director, Tom Hooper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Hooper Context triple: [Red Dust, director, Tom Hooper]
-
A.
Tom Hooper
chosen
Tom Hooper is an Academy Award–winning British film and television director best known for works such as "The King’s Speech" and "Les Misérables."
-
B.
Tom Hooper
Tom Hooper was a prominent early 20th-century Canadian ice hockey player best known for his role with the Kenora Thistles during their Stanley Cup–winning era.
-
C.
Joe Wright
Joe Wright is a British film director best known for acclaimed period dramas such as "Pride & Prejudice" and "Atonement."
-
D.
Sam Mendes
Sam Mendes is an acclaimed British film and theatre director known for works such as "American Beauty," the James Bond films "Skyfall" and "Spectre," and the World War I epic "1917."
-
E.
Stephen Daldry
Stephen Daldry is an acclaimed British theatre and film director and producer known for works such as "Billy Elliot," "The Hours," and "The Reader."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a909785c8190a02b1195eadb384c |
completed | April 20, 2026, 10:30 p.m. |
Created at: April 16, 2026, 11:39 a.m.