Triple
T21787439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herbert Hoover |
E537876
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hoover |
—
|
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: Hoover | Statement: [Herbert Hoover, familyName, Hoover]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoover Context triple: [Herbert Hoover, familyName, Hoover]
-
A.
Hoover
chosen
Hoover is a surname most prominently associated with Herbert Hoover, the 31st president of the United States.
-
B.
Hoover
Hoover is a suburban city in the Birmingham metropolitan area of central Alabama, known for its residential communities and shopping centers like the Riverchase Galleria.
-
C.
Hoovers
Hoovers are British Rail Class 50 diesel-electric locomotives, informally named for the distinctive vacuum-cleaner-like sound of their original cooling fans.
-
D.
The Hoover Company
The Hoover Company is an American manufacturer best known for pioneering and popularizing household vacuum cleaners throughout the 20th century.
-
E.
Roper
Roper is an English surname historically associated with Margaret Roper, the learned daughter of Sir Thomas More.
- 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_69e0c47198f881908cb0d237266c10e9 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0621c68588190977891055e80a499 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 16, 2026, 6:52 p.m.