Triple
T668707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alessandro Volta 10000 lire banknote |
E12923
|
entity |
| Predicate | honouredPersonOccupation |
P18120
|
FINISHED |
| Object | physicist |
—
|
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: physicist | Statement: [Alessandro Volta 10000 lire banknote, honouredPersonOccupation, physicist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honouredPersonOccupation Context triple: [Alessandro Volta 10000 lire banknote, honouredPersonOccupation, physicist]
-
A.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
B.
namedPersonRole
Indicates that a person is identified by name as holding a specific role or position in a given context.
-
C.
notablePersonnel
Indicates that the subject has associated individuals who are particularly important, distinguished, or prominent in relation to it.
-
D.
notableCulturalFigure
Indicates that a person holds significant influence or recognition within a culture’s arts, traditions, values, or public life.
-
E.
occupationOf
Indicates that one entity holds or performs the job, role, or profession associated with another entity.
- F. None of above. chosen
Provenance (4 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49ff921288190a2e5edb201ba69ee |
completed | March 1, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69a49d18942c819083b3d1887e505900 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49fcf0cb4819096edea4037ca2c03 |
completed | March 1, 2026, 8:21 p.m. |
Created at: March 1, 2026, 7:36 p.m.