Triple
T355888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Roebling |
E7540
|
entity |
| Predicate | notableStudentOf |
P4838
|
FINISHED |
| Object | John A. Roebling's engineering methods |
—
|
LITERAL 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 A. Roebling's engineering methods | Statement: [Washington Roebling, notableStudentOf, John A. Roebling's engineering methods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableStudentOf Context triple: [Washington Roebling, notableStudentOf, John A. Roebling's engineering methods]
-
A.
notableStudent
chosen
Indicates that a person is a distinguished or particularly significant student of another individual or institution.
-
B.
hasNotableAlumniType
Indicates that an entity has notable alumni belonging to a specified category or type.
-
C.
notableInstitution
Indicates that an institution holds particular significance, prominence, or recognition in relation to the subject.
-
D.
notableCulturalFigure
Indicates that a person holds significant influence or recognition within a culture’s arts, traditions, values, or public life.
-
E.
notableScientist
Indicates that the subject is a scientist who is widely recognized for significant contributions or impact in their field.
- F. None of above.
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_69a2e7e696948190bebc966535995e45 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebad8bf08190b4a38ffd9157d641 |
completed | Feb. 28, 2026, 1:20 p.m. |
| PD | Predicate disambiguation | batch_69a2e9589e7c8190b2d3af8f858c96af |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.