Triple
T20637075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiram Scott |
E507111
|
entity |
| Predicate | nameVariant |
P744
|
FINISHED |
| Object | Hyram Scott |
—
|
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: Hyram Scott | Statement: [Hiram Scott, nameVariant, Hyram Scott]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hyram Scott Context triple: [Hiram Scott, nameVariant, Hyram Scott]
-
A.
Michael Marks
Michael Marks was a Polish-born British businessman best known as the co-founder of the major retail chain Marks & Spencer.
-
B.
Alfred Fuller
Alfred Fuller was a Canadian-born American entrepreneur best known as the founder of the Fuller Brush Company, a pioneering direct-sales household products business.
-
C.
Hiram Daniel Scott
chosen
Hiram Daniel Scott was a 19th-century American settler and landowner whose ranch formed the basis of what later became Scotts Valley, California.
-
D.
Arthur Wightman
Arthur Wightman was an influential mathematical physicist best known for formulating the Wightman axioms, which provided a rigorous foundation for quantum field theory.
-
E.
Harrington Emerson
Harrington Emerson was an American efficiency engineer and early management consultant known for promoting scientific management and developing principles to improve industrial productivity.
- 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6ad1089448190b936de6fd29c8350 |
completed | April 20, 2026, 10:47 p.m. |
Created at: April 16, 2026, 11:42 a.m.