Triple
T14400256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doc Hollywood |
E357050
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Barnard Hughes |
E686836
|
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: Barnard Hughes | Statement: [Doc Hollywood, starring, Barnard Hughes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barnard Hughes Context triple: [Doc Hollywood, starring, Barnard Hughes]
-
A.
Barnard Hughes
chosen
Barnard Hughes was an American character actor known for his work in film, television, and theater, often playing kindly or eccentric older men.
-
B.
Francis Hughes
Francis Hughes was a Provisional Irish Republican Army volunteer from Northern Ireland who became widely known for dying on hunger strike in the Maze Prison in 1981.
-
C.
Rutherford Alcock
Rutherford Alcock was a 19th-century British diplomat best known as the first British consul in Japan and for helping open the country to Western influence.
-
D.
George Buckley
George Buckley is a British businessman best known for serving as the chairman and CEO of 3M.
-
E.
Sidney Lanfield
Sidney Lanfield was an American film and television director best known for his work on Hollywood comedies and genre films from the 1930s through the 1950s.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de908500048190bb6a20fe318d5c62 |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bbfc6048190897f064a5686ebf8 |
completed | May 9, 2026, 1:19 a.m. |
Created at: April 10, 2026, 1:17 a.m.