Triple
T22442354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Gilmore Backus |
E554783
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Backus |
—
|
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: Backus | Statement: [James Gilmore Backus, familyName, Backus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Backus Context triple: [James Gilmore Backus, familyName, Backus]
-
A.
Backus
chosen
Backus is a surname most notably associated with John Backus, the American computer scientist who led the development of the Fortran programming language.
-
B.
Burrus
Burrus is a variant form of the name Burr, used as a personal or family name.
-
C.
Bonger
Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
-
D.
Bortus
Bortus is a stoic, duty-bound Moclan officer serving as second-in-command aboard the exploratory spaceship in the sci-fi comedy series "The Orville."
-
E.
Earley
Earley is a suburban town in Berkshire, England, situated near Reading and known for its residential character and proximity to major transport links.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae2f7608190b1c1e8bd12ca2162 |
completed | April 29, 2026, 1:12 a.m. |
Created at: April 16, 2026, 8:47 p.m.