Triple
T9937314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In the Land of Blood and Honey |
E193989
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Graham King |
E132899
|
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: Graham King | Statement: [In the Land of Blood and Honey, producer, Graham King]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Graham King Context triple: [In the Land of Blood and Honey, producer, Graham King]
-
A.
Graham King
chosen
Graham King is a British film producer known for acclaimed movies such as "The Departed," "Bohemian Rhapsody," and "The Aviator."
-
B.
Jack Brooksbank
Jack Brooksbank is a British wine merchant and socialite best known as the husband of Princess Eugenie of York.
-
C.
David Heyman
David Heyman is a British film producer best known for originating and producing the Harry Potter film series and other major studio franchises.
-
D.
Mike Donovan
Mike Donovan is a recurring human character in Isaac Asimov’s Robot series, known as a field tester and troubleshooter who works closely with experimental robots.
-
E.
Geoffrey Fletcher
Geoffrey Fletcher is an American screenwriter and filmmaker best known for his Academy Award–winning adapted screenplay for the film "Precious."
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e4e19881909879b394090d6629 |
completed | April 2, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d228f259b081909ce8a90ec1adad0d |
completed | April 5, 2026, 9:18 a.m. |
Created at: March 30, 2026, 8:44 p.m.