Triple
T17205558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Augustus John |
E417591
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Augustus John |
E417591
|
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: Augustus John | Statement: [Augustus John, name, Augustus John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Augustus John Context triple: [Augustus John, name, Augustus John]
-
A.
Augustus John
chosen
Augustus John was a prominent early 20th-century Welsh painter and etcher known for his vivid portraits and bohemian lifestyle.
-
B.
John Lavery
John Lavery was an Irish-born British painter renowned for his society portraits and official war art during the late 19th and early 20th centuries.
-
C.
Rupert Bonington
Rupert Bonington is the son of renowned British mountaineer Sir Chris Bonington.
-
D.
John Wain
John Wain was an English novelist, poet, critic, and member of the postwar "Angry Young Men" literary movement.
-
E.
George Washington Watts
George Washington Watts was an American industrialist and philanthropist best known for helping build the tobacco empire that shaped Durham, North Carolina’s early economic growth.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dc0bea8819090946615a14b2d86 |
completed | April 19, 2026, 1:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fde8ba08190ae88dc9ea3366a68 |
completed | May 11, 2026, 4:49 a.m. |
Created at: April 10, 2026, 5:38 a.m.