Triple
T905556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calvin University |
E19539
|
entity |
| Predicate | academicProgram |
P2489
|
FINISHED |
| Object | liberal arts |
—
|
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: liberal arts | Statement: [Calvin University, academicProgram, liberal arts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicProgram Context triple: [Calvin University, academicProgram, liberal arts]
-
A.
hasEducationalProgram
chosen
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
B.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
C.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
D.
academicAdvisor
Indicates that one entity serves as the academic advisor, providing formal guidance and oversight on academic matters, to another entity.
-
E.
academicType
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3bcad2481908b83575b2fb80d14 |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b28ff5948190982c4439eadf9d87 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:39 p.m.