Triple
T8440540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Hannah |
E199340
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | John Hannah |
E199340
|
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 Hannah | Statement: [John Hannah, name, John Hannah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Hannah Context triple: [John Hannah, name, John Hannah]
-
A.
John Hannah
chosen
John Hannah is a Scottish actor best known for his roles in films such as "Four Weddings and a Funeral" and "The Mummy" series, as well as numerous British television dramas.
-
B.
Jack Hannah
Jack Hannah is an American animator and director best known for his work on classic Walt Disney cartoons, particularly those featuring Donald Duck.
-
C.
Bob Gunton
Bob Gunton is an American character actor best known for his portrayal of the strict prison warden Samuel Norton in the film "The Shawshank Redemption."
-
D.
Thomas Sadoski
Thomas Sadoski is an American actor known for his roles in television series like "The Newsroom" and films such as "John Wick" and "Wild."
-
E.
John Ferrell
John Ferrell was a photographer for the U.S. Farm Security Administration, contributing documentary images of American life during the Great Depression and World War II era.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe138a94081908e306d22aaa39b24 |
completed | March 31, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1d9140b48190ad0c493948a3de5e |
completed | April 2, 2026, 7:41 a.m. |
Created at: March 30, 2026, 6:08 p.m.