Triple
T1095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MIT OpenCourseWare |
E22
|
entity |
| Predicate | businessModel |
P59
|
FINISHED |
| Object | nonprofit |
—
|
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: nonprofit | Statement: [MIT OpenCourseWare, businessModel, nonprofit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessModel Context triple: [MIT OpenCourseWare, businessModel, nonprofit]
-
A.
fundingModel
chosen
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
-
B.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
C.
operatesBy
Indicates that an entity performs its function, action, or process through the use or application of another entity (e.g., a method, mechanism, or principle).
-
D.
commissionedBy
Indicates that one entity has been formally requested, authorized, or hired by another entity to create, perform, or carry out something.
-
E.
website
Indicates that one entity is the official website or web presence associated with another 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_69a22a285828819081a58308fb963df1 |
completed | Feb. 27, 2026, 11:35 p.m. |
| NER | Named-entity recognition | batch_69a23211f05c8190b8deb03a8540d84d |
completed | Feb. 28, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69a230c2c48481908beb1db3cc9768aa |
completed | Feb. 28, 2026, 12:03 a.m. |
Created at: Feb. 27, 2026, 11:36 p.m.