Triple
T33475406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Arts and Sciences (New York Institute of Technology) |
E857306
|
entity |
| Predicate | accreditationBody |
P17719
|
FINISHED |
| Object | Middle States Commission on Higher Education (through NYIT) |
—
|
NE NERFINISHED |
How this triple was built (1 step)
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: Middle States Commission on Higher Education (through NYIT) | Statement: [College of Arts and Sciences (New York Institute of Technology), accreditationBody, Middle States Commission on Higher Education (through NYIT)]
Provenance (2 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_69f3497472508190b300ebd3fd402367 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e501c1fc819081b14287930e834d |
completed | May 3, 2026, 6:02 a.m. |
Created at: May 1, 2026, 1:38 a.m.