Triple
T18273770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UES |
E437678
|
entity |
| Predicate | programDiversity |
P131133
|
FINISHED |
| Object | broad range of academic programs |
—
|
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: broad range of academic programs | Statement: [UES, programDiversity, broad range of academic programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: programDiversity Context triple: [UES, programDiversity, broad range of academic programs]
-
A.
programType
Indicates the category or kind of program to which an entity belongs or with which it is associated.
-
B.
programBasedOn
Indicates that one program is derived from, inspired by, or constructed using the content, structure, or principles of another program or source.
-
C.
madeProgram
Indicates that one entity created, developed, or authored a program (such as software or a coded application).
-
D.
programmingIncludes
Indicates that one programming-related entity contains, incorporates, or makes use of another as a part, feature, or component.
-
E.
inspiredPrograms
Indicates that one entity served as a source of inspiration or influence for the creation or design of another entity’s programs.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5005006108190bbddddbe6bbdc911 |
completed | April 19, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69e44fd81c788190b08c6be3b07a08c5 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:34 a.m.