Triple
T25184103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Life of De Witt Clinton |
E630666
|
entity |
| Predicate | workSubjectOfficeHeld |
P151711
|
FINISHED |
| Object | Governor of New York |
—
|
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: Governor of New York | Statement: [Life of De Witt Clinton, workSubjectOfficeHeld, Governor of New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workSubjectOfficeHeld Context triple: [Life of De Witt Clinton, workSubjectOfficeHeld, Governor of New York]
-
A.
aboutOfficeHeld
Indicates that one entity is related to, or provides information about, a specific office or position that is or was held by another entity.
-
B.
subjectOffice
chosen
Indicates the office or official position held by the subject in relation to another entity or context.
-
C.
natureOfOffice
Indicates the type or character of an office or position, specifying what kind of role or function it represents.
-
D.
typeOfOffice
Indicates the specific category or kind of office that an office entity belongs to (e.g., executive, legislative, judicial, or other office types).
-
E.
officeHeldOf
Indicates that a specific office or position is (or was) held by a particular person or entity.
- 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_69e75a88fdf081908e47ae6e195c14e1 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f48b9b687881908fd87a2f5fa0b1e7 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 12:36 p.m.