Triple
T21511321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sherry |
E530728
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | William Grant Sherry |
—
|
NE NERFINISHED |
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: William Grant Sherry | Statement: [Sherry, usedBy, William Grant Sherry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Grant Sherry Context triple: [Sherry, usedBy, William Grant Sherry]
-
A.
William Grant Sherry
chosen
William Grant Sherry was an American artist and World War II veteran best known as the third husband of actress Bette Davis.
-
B.
William Grant
William Grant was an architect and landscape designer known for his role in shaping the modern layout and features of New York City's Madison Square Park.
-
C.
George Hennessy
George Hennessy was a British Conservative politician who served as a Member of Parliament in the early 20th century.
-
D.
George Hennessy
George Hennessy was a screenwriter active during the early 20th century silent film era.
-
E.
Jes Macallan
Jes Macallan is an American actress best known for her role as Ava Sharpe on the superhero television series DC's Legends of Tomorrow.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea863b18819080e3ff249b10ec28 |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:25 p.m.