Triple
T2221895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Prestige |
E48158
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Emma Thomas |
E42261
|
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: Emma Thomas | Statement: [The Prestige, producer, Emma Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emma Thomas Context triple: [The Prestige, producer, Emma Thomas]
-
A.
Emma Thomas
chosen
Emma Thomas is a British film producer best known for her long-running collaboration with director Christopher Nolan on major films such as Inception, The Dark Knight trilogy, and Oppenheimer.
-
B.
Rosie Thomas
Rosie Thomas is an American singer-songwriter known for her delicate, introspective indie folk music and collaborations within the Seattle music scene.
-
C.
Samantha Thompson
Samantha Thompson is known as the daughter of American politician and former Illinois governor James R. Thompson.
-
D.
Sarah Thorne
Sarah Thorne was the wife of Leonard Darwin, son of the naturalist Charles Darwin.
-
E.
Mia Dolan
Mia Dolan is an aspiring actress in Los Angeles and one of the two central protagonists of the musical film "La La Land."
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03bfdd48190bfb96ec3e41c22dc |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1f74880481908ffd16a25792f013 |
completed | March 9, 2026, 7:28 p.m. |
Created at: March 4, 2026, 7:47 p.m.