Triple
T27854270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Foundation for Excellence in Education |
E704040
|
entity |
| Predicate | founderOfficeHeld |
P181311
|
FINISHED |
| Object | Governor of Florida |
—
|
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 Florida | Statement: [Foundation for Excellence in Education, founderOfficeHeld, Governor of Florida]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: founderOfficeHeld Context triple: [Foundation for Excellence in Education, founderOfficeHeld, Governor of Florida]
-
A.
firstOfficeHolder
Indicates that the subject is the very first individual to hold a particular office or position associated with the object.
-
B.
establishedOffice
Indicates that an entity created or set up an official office or place of operation.
-
C.
headquartersOfOffice
Indicates that a particular location serves as the main headquarters for a specified office or organizational unit.
-
D.
headquartersFoundedAt
Indicates that an organization's headquarters was originally established at a specific location.
-
E.
founder
Indicates that an entity established, created, or started another entity such as an organization, institution, or company.
- 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_69ef840e614c8190a88cf9638c14a265 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
| PDg | Predicate description generation | batch_69f7688cea58819098bdfd7c80df7634 |
completed | May 3, 2026, 3:23 p.m. |
Created at: April 27, 2026, 6:13 p.m.