Triple
T6689763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Canyon University |
E152593
|
entity |
| Predicate | sectorHistory |
P28623
|
FINISHED |
| Object | transitioned from for-profit to nonprofit status |
—
|
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: transitioned from for-profit to nonprofit status | Statement: [Grand Canyon University, sectorHistory, transitioned from for-profit to nonprofit status]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorHistory Context triple: [Grand Canyon University, sectorHistory, transitioned from for-profit to nonprofit status]
-
A.
regionHistory
Indicates that there exists a historical or past association between a subject and a specific geographic or administrative region.
-
B.
historicalStatusOf
chosen
Indicates the historical condition, role, or classification that an entity held during a specific past period or context.
-
C.
hasHistoricIndustry
Indicates that an entity has been associated with a notable or historically significant industry or industrial activity in the past.
-
D.
historicalType
Indicates that one entity classifies or characterizes another in terms of its role, status, or category within a historical context.
-
E.
sponsorHistory
Indicates that one entity has previously acted as a sponsor for another entity or event over time.
- 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_69c6880687b08190805278b504d1c92c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cd0fa5188190a23281cb09d98139 |
completed | March 27, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0d3c1081908dadff7a6a054123 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:04 p.m.