Triple
T1951985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Message from the King |
E42178
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
David Lancaster
David Lancaster is a film producer known for his work on independent and genre films, including the thriller "Message from the King."
|
E222389
|
NE FINISHED |
How this triple was built (4 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: David Lancaster | Statement: [Message from the King, producer, David Lancaster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Lancaster Context triple: [Message from the King, producer, David Lancaster]
-
A.
John Leeson
John Leeson is a British actor best known for voicing the robotic dog K-9 in the Doctor Who television franchise.
-
B.
Robert Hinde
Robert Hinde was a British zoologist and ethologist renowned for his pioneering research on animal behavior and social relationships, and for mentoring influential primatologists such as Jane Goodall.
-
C.
Richard Hiscott
Richard Hiscott is an editor known for his work on the television series "Willow."
-
D.
Geoffrey Smith
Geoffrey Smith is an Australian Anglican archbishop who serves as the national leader (Primate) of the Anglican Church of Australia.
-
E.
Nigel Shadbolt
Nigel Shadbolt is a British computer scientist and artificial intelligence researcher known for his leading role in promoting open data and digital governance.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: David Lancaster Triple: [Message from the King, producer, David Lancaster]
Generated description
David Lancaster is a film producer known for his work on independent and genre films, including the thriller "Message from the King."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David Lancaster Target entity description: David Lancaster is a film producer known for his work on independent and genre films, including the thriller "Message from the King."
-
A.
John Leeson
John Leeson is a British actor best known for voicing the robotic dog K-9 in the Doctor Who television franchise.
-
B.
Robert Hinde
Robert Hinde was a British zoologist and ethologist renowned for his pioneering research on animal behavior and social relationships, and for mentoring influential primatologists such as Jane Goodall.
-
C.
Richard Hiscott
Richard Hiscott is an editor known for his work on the television series "Willow."
-
D.
Geoffrey Smith
Geoffrey Smith is an Australian Anglican archbishop who serves as the national leader (Primate) of the Anglican Church of Australia.
-
E.
Nigel Shadbolt
Nigel Shadbolt is a British computer scientist and artificial intelligence researcher known for his leading role in promoting open data and digital governance.
- F. None of above. chosen
Provenance (5 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb34eb5748190a3ac395252951eba |
completed | March 7, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae031a46d481908a6e0d78bfa9c66f |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae03c4faac8190a13aa0882eda3629 |
completed | March 8, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae044314188190a7472cf5f8e89f6c |
completed | March 8, 2026, 11:20 p.m. |
Created at: March 4, 2026, 7:36 p.m.