Triple
T3575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Association of Independent Technological Universities |
E67
|
entity |
| Predicate | collaboratesOn |
P37
|
FINISHED |
| Object | technological education initiatives |
—
|
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: technological education initiatives | Statement: [Association of Independent Technological Universities, collaboratesOn, technological education initiatives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collaboratesOn Context triple: [Association of Independent Technological Universities, collaboratesOn, technological education initiatives]
-
A.
proposes
Indicates that one entity formally suggests or puts forward an idea, plan, or course of action to another entity for consideration or approval.
-
B.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
-
C.
commissionedBy
Indicates that one entity has been formally requested, authorized, or hired by another entity to create, perform, or carry out something.
-
D.
notableWork
Indicates that one entity is a significant or well-known work (such as a book, artwork, or creation) produced by another entity.
-
E.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a23bcc8eb48190b897cc331563980a |
completed | Feb. 28, 2026, 12:50 a.m. |
| PD | Predicate disambiguation | batch_69a23994309081909ff3e869deef2156 |
completed | Feb. 28, 2026, 12:40 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.