Triple
T12836074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Hoyland |
E306916
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | John Hoyland |
E306916
|
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: John Hoyland | Statement: [John Hoyland, name, John Hoyland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Hoyland Context triple: [John Hoyland, name, John Hoyland]
-
A.
John Hoyland
chosen
John Hoyland was a prominent British abstract painter known for his bold use of color and large-scale, non-figurative works.
-
B.
John Hollowood
John Hollowood is a businessman known for being one of the founders of the multinational chemicals company Ineos.
-
C.
John Wenham
John Wenham was a 20th-century British evangelical biblical scholar best known for his conservative New Testament scholarship and advocacy of the Augustinian hypothesis regarding the Synoptic Gospels.
-
D.
Ray Deakin
Ray Deakin was an English professional footballer, best known as a tough-tackling defender whose performances earned him recognition in the Bolton Wanderers Hall of Fame.
-
E.
Gordon Hales
Gordon Hales was a film editor known for his work on major British and international productions, including Charlie Chaplin’s final film "A Countess from Hong Kong."
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff015f4819090070a01f3938acc |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7396b901c81908bfac5b40e3caed4 |
completed | May 3, 2026, 12:02 p.m. |
Created at: April 9, 2026, 5:35 p.m.