Triple
T14848479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Foyle |
E349162
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Michael Kitchen |
E226083
|
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: Michael Kitchen | Statement: [Christopher Foyle, portrayedBy, Michael Kitchen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Kitchen Context triple: [Christopher Foyle, portrayedBy, Michael Kitchen]
-
A.
Michael Kitchen
chosen
Michael Kitchen is a British actor best known for his versatile film and television roles, including the lead in the detective series "Foyle's War."
-
B.
Michael Gunton
Michael Gunton is a British television producer best known for his work on major BBC natural history series such as Planet Earth II and Dynasties.
-
C.
Michael Sims
Michael Sims is an American author and essayist known for his works on nature, science, and cultural history.
-
D.
Michael Hurd
Michael Hurd is a British composer and musicologist best known for his choral works, educational music, and accessible compositions for amateur performers.
-
E.
John Seitz
John Seitz was an American cinematographer renowned for his influential work in classic Hollywood cinema, particularly in film noir and science fiction.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded29236dc8190b7d3a37d09f9fb21 |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6502d3f081909ff6fa8722769e2e |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:53 a.m.