Triple
T8017413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keen |
E186652
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Malcolm Keen |
E394464
|
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: Malcolm Keen | Statement: [Keen, hasNotableBearer, Malcolm Keen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malcolm Keen Context triple: [Keen, hasNotableBearer, Malcolm Keen]
-
A.
Malcolm Keen
chosen
Malcolm Keen was a British actor known for his work in early 20th-century stage and silent films, including collaborations with director Alfred Hitchcock.
-
B.
Lionel W. McKenzie
Lionel W. McKenzie was an American economist best known for his rigorous mathematical contributions to general equilibrium theory and the formalization of modern microeconomics.
-
C.
Graham Stanton
Graham Stanton is a senior Royal Air Force officer who served as Air Officer Commanding-in-Chief of Fighter Command.
-
D.
John Leeson
John Leeson is a British actor best known for voicing the robotic dog K-9 in the Doctor Who television franchise.
-
E.
Richard G. Wilkinson
Richard G. Wilkinson is a British social epidemiologist known for his influential research on income inequality and its effects on health and social outcomes.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3df4f1b8819089a8b67f136bce9a |
completed | March 31, 2026, 3:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56c213ec8190b3bd96c42d1357e4 |
completed | March 31, 2026, 11:20 p.m. |
Created at: March 30, 2026, 5:20 p.m.