Triple
T10892584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LaRue |
E257216
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | John LaRue |
E194241
|
NE FINISHED |
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: John LaRue | Statement: [LaRue, hasNotableBearer, John LaRue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John LaRue Context triple: [LaRue, hasNotableBearer, John LaRue]
-
A.
John LaRue
chosen
John LaRue was an early American pioneer and landowner in Kentucky after whom LaRue County was named.
-
B.
Daniel Lothrop
Daniel Lothrop was a 19th-century American publisher best known for founding the D. Lothrop Company, which specialized in children's and religious literature.
-
C.
Don LaRue
Don LaRue is an individual notable enough to be recognized as a prominent bearer of the surname LaRue.
-
D.
Lewis Branscomb
Lewis Branscomb was an American physicist and influential science and technology policy leader known for his work at the intersection of research, innovation, and public policy.
-
E.
Henry McMorran
Henry McMorran was a prominent local figure and benefactor in Port Huron, Michigan, whose contributions to the community led to the city’s main event center being named in his honor.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75206354881908b148f2df3938513 |
completed | April 9, 2026, 7:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d6d70e90819093ced18f59785ab9 |
completed | April 18, 2026, 12:56 a.m. |
Created at: April 8, 2026, 9:21 p.m.