Triple
T33333747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States one-dollar bill (1860s series, as Treasury Secretary) |
E853479
|
entity |
| Predicate | officeHeldByDepictedFigure |
P200006
|
FINISHED |
| Object | Treasury Secretary |
—
|
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: Treasury Secretary | Statement: [United States one-dollar bill (1860s series, as Treasury Secretary), officeHeldByDepictedFigure, Treasury Secretary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHeldByDepictedFigure Context triple: [United States one-dollar bill (1860s series, as Treasury Secretary), officeHeldByDepictedFigure, Treasury Secretary]
-
A.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
B.
officeHolderIs
Indicates that one entity serves as the office holder (e.g., official or position occupant) of another entity, such as an office, role, or institution.
-
C.
officeHeldByActor
Indicates that a specific office, position, or role is held or occupied by a particular actor.
-
D.
keyFigureHeldOffice
Indicates that a key figure occupied or served in a particular official position or office.
-
E.
officeHoldersWere
Indicates that certain individuals held specific offices or positions during a particular time or context.
- 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_69f34969614c81909cd99661b0902533 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff6a4ce9a08190b98abde3a170dd69 |
completed | May 9, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69ff69c11634819089d1084bd2c11534 |
completed | May 9, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69ff6a4c32dc819097f591944bee8851 |
completed | May 9, 2026, 5:09 p.m. |
Created at: May 1, 2026, 1:34 a.m.