Triple
T499016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iain Canning |
E10357
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Tom Hooper |
E11868
|
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: Tom Hooper | Statement: [Iain Canning, collaboratedWith, Tom Hooper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Hooper Context triple: [Iain Canning, collaboratedWith, 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.
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."
-
C.
Danny Boyle
Danny Boyle is an acclaimed British film director and producer known for movies such as "Trainspotting," "Slumdog Millionaire," and "28 Days Later."
-
D.
Mark Robson
Mark Robson was a Canadian-born film editor-turned-director known for his work in Hollywood on acclaimed films from the 1940s through the 1960s.
-
E.
Sam Wood
Sam Wood was an American film director best known for his work during Hollywood’s Golden Age, including classics such as "A Night at the Opera," "Goodbye, Mr. Chips," and "The Pride of the Yankees."
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f119b14c8190a5a6b119579c2682 |
completed | Feb. 28, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a481f1ee28819087e90028b89e877e |
completed | March 1, 2026, 6:14 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.