Triple
T2351834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penny Dreadful |
E47464
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Sam Mendes |
E50284
|
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: Sam Mendes | Statement: [Penny Dreadful, executiveProducer, Sam Mendes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sam Mendes Context triple: [Penny Dreadful, executiveProducer, Sam Mendes]
-
A.
Sam Mendes
chosen
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."
-
B.
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."
-
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.
William Oldroyd
William Oldroyd is a British film and theatre director best known for his critically acclaimed 2016 period drama film "Lady Macbeth."
-
E.
Tom Hooper
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."
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc6f8ff548190b07505310e2bf0b9 |
completed | March 7, 2026, 6:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf2eb7a88190b421df42acbd974b |
completed | March 9, 2026, 12:38 p.m. |
Created at: March 4, 2026, 7:54 p.m.