Triple
T17845841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edna May Oliver |
E445656
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Nutter |
—
|
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: Nutter | Statement: [Edna May Oliver, familyName, Nutter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nutter Context triple: [Edna May Oliver, familyName, Nutter]
-
A.
Nutter
Nutter is a small village in the Dutch province of Overijssel, known for its rural landscape and traditional countryside character.
-
B.
Nutter
chosen
Nutter is a surname most notably associated with Michael Nutter, the former mayor of Philadelphia.
-
C.
Nutt
Nutt is a surname most notably associated with David Nutt, a British neuropsychopharmacologist known for his research on the effects of drugs on the brain and for advising on drug policy.
-
D.
Dunnigan
Dunnigan is a small unincorporated community in Yolo County, California, known primarily as a rural agricultural area along Interstate 5.
-
E.
Filbert
Filbert is the anthropomorphic fox mascot of the Leicester City Football Club, commonly seen entertaining fans at the team’s matches and events.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffa4c648190a88a4b0733493d91 |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:16 a.m.